Token Classification
ONNX
multilingual
glitext
rpeel commited on
Commit
c715585
·
verified ·
1 Parent(s): 4d09206

Update model card and security scan results

Browse files
Files changed (2) hide show
  1. README.md +38 -7
  2. modelaudit.json +1073 -0
README.md CHANGED
@@ -1,22 +1,53 @@
1
  ---
2
  library_name: glitext
 
3
  tags:
4
- - glitext
5
  glitext:
6
- name: "medium"
7
- label: "GliText Recognition (Balanced)"
8
- description: "An efficient zero-shot named entity recognition model tuned for generalized extraction with balanced speed and accuracy."
9
  recognition: true
10
  classification: false
11
  association: false
12
  span_mode: true
13
  size_gb: 0.78
14
- hf_repo: "rpeel/glitext-medium"
15
- source_url: "gliner-community/gliner_medium-v2.5"
16
  ---
17
 
18
  # rpeel/glitext-medium
19
 
20
  An efficient zero-shot named entity recognition model tuned for generalized extraction with balanced speed and accuracy.
21
 
22
- This model is managed by the GLiText server. Download it via the Models page.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
  library_name: glitext
3
+ license: apache-2.0
4
  tags:
5
+ - glitext
6
  glitext:
7
+ name: medium
8
+ label: GliText Recognition (Balanced)
9
+ description: An efficient zero-shot named entity recognition model tuned for generalized extraction with balanced speed and accuracy.
10
  recognition: true
11
  classification: false
12
  association: false
13
  span_mode: true
14
  size_gb: 0.78
15
+ hf_repo: rpeel/glitext-medium
16
+ source_url: gliner-community/gliner_medium-v2.5
17
  ---
18
 
19
  # rpeel/glitext-medium
20
 
21
  An efficient zero-shot named entity recognition model tuned for generalized extraction with balanced speed and accuracy.
22
 
23
+ ## Requirements
24
+
25
+ To download this model to the SAS GLiText server:
26
+
27
+ ```
28
+ POST /v1/models/download?name=medium
29
+ ```
30
+
31
+ To download and load into memory in one step:
32
+
33
+ ```
34
+ PUT /v1/models?name=medium
35
+ ```
36
+
37
+ ## Source Model
38
+
39
+ Exported from [gliner-community/gliner_medium-v2.5](https://huggingface.co/gliner-community/gliner_medium-v2.5).
40
+ See the [original model card](https://huggingface.co/gliner-community/gliner_medium-v2.5) for full architecture and training details.
41
+
42
+ ## Security Scan
43
+
44
+ Scanned with [modelaudit](https://github.com/promptfoo/modelaudit) v0.2.40 on 2026-04-27. 24/24 checks passed. [Full results](modelaudit.json).
45
+
46
+
47
+ | File | Size | SHA-256 |
48
+ |------|------|---------|
49
+ | `model.onnx` | 835.6 MB | `dfbf82b4c9b7cb8e…` |
50
+
51
+ ## License
52
+
53
+ [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0). Derived from [gliner-community/gliner_medium-v2.5](https://huggingface.co/gliner-community/gliner_medium-v2.5) by [gliner-community](https://huggingface.co/gliner-community).
modelaudit.json ADDED
@@ -0,0 +1,1073 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "tool": "modelaudit",
3
+ "tool_version": "0.2.40",
4
+ "scanned_at": "2026-04-27T00:38:25Z",
5
+ "files": {
6
+ "model.onnx": {
7
+ "size_mb": 835.6,
8
+ "sha256": "dfbf82b4c9b7cb8ebedb6e04bec068db7cfee3053cb90c7d4aa11b8a93edb46a"
9
+ }
10
+ },
11
+ "audit": {
12
+ "bytes_scanned": 843939140,
13
+ "issues": [
14
+ {
15
+ "message": "Weight distribution analysis skipped one or more eligible ONNX initializers",
16
+ "severity": "info",
17
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
18
+ "details": {
19
+ "scan_outcome_reason": "onnx_weight_distribution_analysis_incomplete",
20
+ "coverage_gap": "partial_initializer_coverage",
21
+ "eligible_initializers": 85,
22
+ "analyzed_initializers": 84,
23
+ "external_initializers_skipped": 0,
24
+ "oversized_initializers_skipped": 1,
25
+ "extraction_failures": 0,
26
+ "max_array_size": 104857600
27
+ },
28
+ "timestamp": 1777250300.2642596,
29
+ "type": "onnx_check",
30
+ "rule_code": "S902"
31
+ },
32
+ {
33
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 7 has unusually dissimilar weights",
34
+ "severity": "info",
35
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
36
+ "details": {
37
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
38
+ "neuron_index": 7,
39
+ "max_similarity_to_others": 0.6353273391723633,
40
+ "weight_norm": 5.372602462768555,
41
+ "total_outputs": 768,
42
+ "analysis_method": "structural_analysis"
43
+ },
44
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
45
+ "timestamp": 1777250303.1872206,
46
+ "type": "onnx_check",
47
+ "rule_code": "S803"
48
+ },
49
+ {
50
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 48 has unusually dissimilar weights",
51
+ "severity": "info",
52
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
53
+ "details": {
54
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
55
+ "neuron_index": 48,
56
+ "max_similarity_to_others": 0.6696844100952148,
57
+ "weight_norm": 0.46152299642562866,
58
+ "total_outputs": 768,
59
+ "analysis_method": "structural_analysis"
60
+ },
61
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
62
+ "timestamp": 1777250303.1879716,
63
+ "type": "onnx_check",
64
+ "rule_code": "S803"
65
+ },
66
+ {
67
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 117 has unusually dissimilar weights",
68
+ "severity": "info",
69
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
70
+ "details": {
71
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
72
+ "neuron_index": 117,
73
+ "max_similarity_to_others": 0.634371280670166,
74
+ "weight_norm": 0.39997434616088867,
75
+ "total_outputs": 768,
76
+ "analysis_method": "structural_analysis"
77
+ },
78
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
79
+ "timestamp": 1777250303.1885126,
80
+ "type": "onnx_check",
81
+ "rule_code": "S803"
82
+ },
83
+ {
84
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 213 has unusually dissimilar weights",
85
+ "severity": "info",
86
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
87
+ "details": {
88
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
89
+ "neuron_index": 213,
90
+ "max_similarity_to_others": 0.6954333186149597,
91
+ "weight_norm": 0.5225619673728943,
92
+ "total_outputs": 768,
93
+ "analysis_method": "structural_analysis"
94
+ },
95
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
96
+ "timestamp": 1777250303.1890316,
97
+ "type": "onnx_check",
98
+ "rule_code": "S803"
99
+ },
100
+ {
101
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 248 has unusually dissimilar weights",
102
+ "severity": "info",
103
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
104
+ "details": {
105
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
106
+ "neuron_index": 248,
107
+ "max_similarity_to_others": 0.6133643388748169,
108
+ "weight_norm": 0.47258928418159485,
109
+ "total_outputs": 768,
110
+ "analysis_method": "structural_analysis"
111
+ },
112
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
113
+ "timestamp": 1777250303.1895173,
114
+ "type": "onnx_check",
115
+ "rule_code": "S803"
116
+ },
117
+ {
118
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 266 has unusually dissimilar weights",
119
+ "severity": "info",
120
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
121
+ "details": {
122
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
123
+ "neuron_index": 266,
124
+ "max_similarity_to_others": 0.649356484413147,
125
+ "weight_norm": 0.683588981628418,
126
+ "total_outputs": 768,
127
+ "analysis_method": "structural_analysis"
128
+ },
129
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
130
+ "timestamp": 1777250303.1900122,
131
+ "type": "onnx_check",
132
+ "rule_code": "S803"
133
+ },
134
+ {
135
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 272 has unusually dissimilar weights",
136
+ "severity": "info",
137
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
138
+ "details": {
139
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
140
+ "neuron_index": 272,
141
+ "max_similarity_to_others": 0.6721497178077698,
142
+ "weight_norm": 0.4996761083602905,
143
+ "total_outputs": 768,
144
+ "analysis_method": "structural_analysis"
145
+ },
146
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
147
+ "timestamp": 1777250303.1905012,
148
+ "type": "onnx_check",
149
+ "rule_code": "S803"
150
+ },
151
+ {
152
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 296 has unusually dissimilar weights",
153
+ "severity": "info",
154
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
155
+ "details": {
156
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
157
+ "neuron_index": 296,
158
+ "max_similarity_to_others": 0.6973440647125244,
159
+ "weight_norm": 0.5266340374946594,
160
+ "total_outputs": 768,
161
+ "analysis_method": "structural_analysis"
162
+ },
163
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
164
+ "timestamp": 1777250303.1910307,
165
+ "type": "onnx_check",
166
+ "rule_code": "S803"
167
+ },
168
+ {
169
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 329 has unusually dissimilar weights",
170
+ "severity": "info",
171
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
172
+ "details": {
173
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
174
+ "neuron_index": 329,
175
+ "max_similarity_to_others": 0.6732807159423828,
176
+ "weight_norm": 0.7019028663635254,
177
+ "total_outputs": 768,
178
+ "analysis_method": "structural_analysis"
179
+ },
180
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
181
+ "timestamp": 1777250303.191509,
182
+ "type": "onnx_check",
183
+ "rule_code": "S803"
184
+ },
185
+ {
186
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 344 has unusually dissimilar weights",
187
+ "severity": "info",
188
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
189
+ "details": {
190
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
191
+ "neuron_index": 344,
192
+ "max_similarity_to_others": 0.5913342237472534,
193
+ "weight_norm": 1.2862828969955444,
194
+ "total_outputs": 768,
195
+ "analysis_method": "structural_analysis"
196
+ },
197
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
198
+ "timestamp": 1777250303.1919985,
199
+ "type": "onnx_check",
200
+ "rule_code": "S803"
201
+ },
202
+ {
203
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 357 has unusually dissimilar weights",
204
+ "severity": "info",
205
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
206
+ "details": {
207
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
208
+ "neuron_index": 357,
209
+ "max_similarity_to_others": 0.6641792058944702,
210
+ "weight_norm": 0.5504754185676575,
211
+ "total_outputs": 768,
212
+ "analysis_method": "structural_analysis"
213
+ },
214
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
215
+ "timestamp": 1777250303.192473,
216
+ "type": "onnx_check",
217
+ "rule_code": "S803"
218
+ },
219
+ {
220
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 378 has unusually dissimilar weights",
221
+ "severity": "info",
222
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
223
+ "details": {
224
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
225
+ "neuron_index": 378,
226
+ "max_similarity_to_others": 0.5857805609703064,
227
+ "weight_norm": 0.5392732620239258,
228
+ "total_outputs": 768,
229
+ "analysis_method": "structural_analysis"
230
+ },
231
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
232
+ "timestamp": 1777250303.1929657,
233
+ "type": "onnx_check",
234
+ "rule_code": "S803"
235
+ },
236
+ {
237
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 426 has unusually dissimilar weights",
238
+ "severity": "info",
239
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
240
+ "details": {
241
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
242
+ "neuron_index": 426,
243
+ "max_similarity_to_others": 0.6619596481323242,
244
+ "weight_norm": 0.4695207178592682,
245
+ "total_outputs": 768,
246
+ "analysis_method": "structural_analysis"
247
+ },
248
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
249
+ "timestamp": 1777250303.1934395,
250
+ "type": "onnx_check",
251
+ "rule_code": "S803"
252
+ },
253
+ {
254
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 438 has unusually dissimilar weights",
255
+ "severity": "info",
256
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
257
+ "details": {
258
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
259
+ "neuron_index": 438,
260
+ "max_similarity_to_others": 0.6229392290115356,
261
+ "weight_norm": 0.43737903237342834,
262
+ "total_outputs": 768,
263
+ "analysis_method": "structural_analysis"
264
+ },
265
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
266
+ "timestamp": 1777250303.1939251,
267
+ "type": "onnx_check",
268
+ "rule_code": "S803"
269
+ },
270
+ {
271
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 455 has unusually dissimilar weights",
272
+ "severity": "info",
273
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
274
+ "details": {
275
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
276
+ "neuron_index": 455,
277
+ "max_similarity_to_others": 0.6861489415168762,
278
+ "weight_norm": 0.500296413898468,
279
+ "total_outputs": 768,
280
+ "analysis_method": "structural_analysis"
281
+ },
282
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
283
+ "timestamp": 1777250303.1944077,
284
+ "type": "onnx_check",
285
+ "rule_code": "S803"
286
+ },
287
+ {
288
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 481 has unusually dissimilar weights",
289
+ "severity": "info",
290
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
291
+ "details": {
292
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
293
+ "neuron_index": 481,
294
+ "max_similarity_to_others": 0.6357624530792236,
295
+ "weight_norm": 0.589555561542511,
296
+ "total_outputs": 768,
297
+ "analysis_method": "structural_analysis"
298
+ },
299
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
300
+ "timestamp": 1777250303.1949005,
301
+ "type": "onnx_check",
302
+ "rule_code": "S803"
303
+ },
304
+ {
305
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 487 has unusually dissimilar weights",
306
+ "severity": "info",
307
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
308
+ "details": {
309
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
310
+ "neuron_index": 487,
311
+ "max_similarity_to_others": 0.6871294975280762,
312
+ "weight_norm": 0.47944051027297974,
313
+ "total_outputs": 768,
314
+ "analysis_method": "structural_analysis"
315
+ },
316
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
317
+ "timestamp": 1777250303.195397,
318
+ "type": "onnx_check",
319
+ "rule_code": "S803"
320
+ },
321
+ {
322
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 544 has unusually dissimilar weights",
323
+ "severity": "info",
324
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
325
+ "details": {
326
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
327
+ "neuron_index": 544,
328
+ "max_similarity_to_others": 0.6773201823234558,
329
+ "weight_norm": 0.5820121169090271,
330
+ "total_outputs": 768,
331
+ "analysis_method": "structural_analysis"
332
+ },
333
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
334
+ "timestamp": 1777250303.195918,
335
+ "type": "onnx_check",
336
+ "rule_code": "S803"
337
+ },
338
+ {
339
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 719 has unusually dissimilar weights",
340
+ "severity": "info",
341
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
342
+ "details": {
343
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
344
+ "neuron_index": 719,
345
+ "max_similarity_to_others": 0.6987954378128052,
346
+ "weight_norm": 0.7778415083885193,
347
+ "total_outputs": 768,
348
+ "analysis_method": "structural_analysis"
349
+ },
350
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
351
+ "timestamp": 1777250303.1964004,
352
+ "type": "onnx_check",
353
+ "rule_code": "S803"
354
+ },
355
+ {
356
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 729 has unusually dissimilar weights",
357
+ "severity": "info",
358
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
359
+ "details": {
360
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
361
+ "neuron_index": 729,
362
+ "max_similarity_to_others": 0.6774657964706421,
363
+ "weight_norm": 0.6795850396156311,
364
+ "total_outputs": 768,
365
+ "analysis_method": "structural_analysis"
366
+ },
367
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
368
+ "timestamp": 1777250303.1969016,
369
+ "type": "onnx_check",
370
+ "rule_code": "S803"
371
+ },
372
+ {
373
+ "message": "Layer 'core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight' output neuron 739 has unusually dissimilar weights",
374
+ "severity": "info",
375
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
376
+ "details": {
377
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
378
+ "neuron_index": 739,
379
+ "max_similarity_to_others": 0.6594510674476624,
380
+ "weight_norm": 0.8022450804710388,
381
+ "total_outputs": 768,
382
+ "analysis_method": "structural_analysis"
383
+ },
384
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
385
+ "timestamp": 1777250303.1973808,
386
+ "type": "onnx_check",
387
+ "rule_code": "S803"
388
+ }
389
+ ],
390
+ "checks": [
391
+ {
392
+ "name": "Path Exists",
393
+ "status": "passed",
394
+ "message": "Path exists",
395
+ "location": "/opt/sas/model-gli-text/models/medium/README.md",
396
+ "details": {
397
+ "path": "/opt/sas/model-gli-text/models/medium/README.md"
398
+ },
399
+ "timestamp": 1777249824.745477
400
+ },
401
+ {
402
+ "name": "Path Readable",
403
+ "status": "passed",
404
+ "message": "Path is readable",
405
+ "location": "/opt/sas/model-gli-text/models/medium/README.md",
406
+ "details": {
407
+ "path": "/opt/sas/model-gli-text/models/medium/README.md"
408
+ },
409
+ "timestamp": 1777249824.7455053
410
+ },
411
+ {
412
+ "name": "File Type Validation",
413
+ "status": "passed",
414
+ "message": "File type validation passed",
415
+ "location": "/opt/sas/model-gli-text/models/medium/README.md",
416
+ "details": {},
417
+ "timestamp": 1777249824.7455347
418
+ },
419
+ {
420
+ "name": "Path Exists",
421
+ "status": "passed",
422
+ "message": "Path exists",
423
+ "location": "/opt/sas/model-gli-text/models/medium/gliner_config.json",
424
+ "details": {
425
+ "path": "/opt/sas/model-gli-text/models/medium/gliner_config.json"
426
+ },
427
+ "timestamp": 1777249824.7813027
428
+ },
429
+ {
430
+ "name": "Path Readable",
431
+ "status": "passed",
432
+ "message": "Path is readable",
433
+ "location": "/opt/sas/model-gli-text/models/medium/gliner_config.json",
434
+ "details": {
435
+ "path": "/opt/sas/model-gli-text/models/medium/gliner_config.json"
436
+ },
437
+ "timestamp": 1777249824.7813318
438
+ },
439
+ {
440
+ "name": "File Type Validation",
441
+ "status": "passed",
442
+ "message": "File type validation passed",
443
+ "location": "/opt/sas/model-gli-text/models/medium/gliner_config.json",
444
+ "details": {},
445
+ "timestamp": 1777249824.7813616
446
+ },
447
+ {
448
+ "name": "Model Name Policy Check",
449
+ "status": "passed",
450
+ "message": "Model Name Policy Check completed successfully",
451
+ "location": "/opt/sas/model-gli-text/models/medium/gliner_config.json",
452
+ "details": {
453
+ "component_count": 2
454
+ },
455
+ "timestamp": 1777249824.7826722
456
+ },
457
+ {
458
+ "name": "Path Exists",
459
+ "status": "passed",
460
+ "message": "Path exists",
461
+ "location": "/opt/sas/model-gli-text/models/medium/tokenizer_config.json",
462
+ "details": {
463
+ "path": "/opt/sas/model-gli-text/models/medium/tokenizer_config.json"
464
+ },
465
+ "timestamp": 1777249824.8342366
466
+ },
467
+ {
468
+ "name": "Path Readable",
469
+ "status": "passed",
470
+ "message": "Path is readable",
471
+ "location": "/opt/sas/model-gli-text/models/medium/tokenizer_config.json",
472
+ "details": {
473
+ "path": "/opt/sas/model-gli-text/models/medium/tokenizer_config.json"
474
+ },
475
+ "timestamp": 1777249824.83427
476
+ },
477
+ {
478
+ "name": "File Type Validation",
479
+ "status": "passed",
480
+ "message": "File type validation passed",
481
+ "location": "/opt/sas/model-gli-text/models/medium/tokenizer_config.json",
482
+ "details": {},
483
+ "timestamp": 1777249824.8343112
484
+ },
485
+ {
486
+ "name": "Template Extraction",
487
+ "status": "passed",
488
+ "message": "No Jinja2 templates found in file",
489
+ "location": "/opt/sas/model-gli-text/models/medium/tokenizer_config.json",
490
+ "details": {
491
+ "file_type": "tokenizer_config"
492
+ },
493
+ "timestamp": 1777249824.8348958
494
+ },
495
+ {
496
+ "name": "Path Exists",
497
+ "status": "passed",
498
+ "message": "Path exists",
499
+ "location": "/opt/sas/model-gli-text/models/medium/tokenizer.json",
500
+ "details": {
501
+ "path": "/opt/sas/model-gli-text/models/medium/tokenizer.json"
502
+ },
503
+ "timestamp": 1777249826.885802
504
+ },
505
+ {
506
+ "name": "Path Readable",
507
+ "status": "passed",
508
+ "message": "Path is readable",
509
+ "location": "/opt/sas/model-gli-text/models/medium/tokenizer.json",
510
+ "details": {
511
+ "path": "/opt/sas/model-gli-text/models/medium/tokenizer.json"
512
+ },
513
+ "timestamp": 1777249826.8858373
514
+ },
515
+ {
516
+ "name": "File Type Validation",
517
+ "status": "passed",
518
+ "message": "File type validation passed",
519
+ "location": "/opt/sas/model-gli-text/models/medium/tokenizer.json",
520
+ "details": {},
521
+ "timestamp": 1777249826.8858702
522
+ },
523
+ {
524
+ "name": "Template Extraction",
525
+ "status": "passed",
526
+ "message": "No Jinja2 templates found in file",
527
+ "location": "/opt/sas/model-gli-text/models/medium/tokenizer.json",
528
+ "details": {
529
+ "file_type": "tokenizer_config"
530
+ },
531
+ "timestamp": 1777249827.3324003
532
+ },
533
+ {
534
+ "name": "Path Exists",
535
+ "status": "passed",
536
+ "message": "Path exists",
537
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
538
+ "details": {
539
+ "path": "/opt/sas/model-gli-text/models/medium/model.onnx"
540
+ },
541
+ "timestamp": 1777249827.3575664
542
+ },
543
+ {
544
+ "name": "Path Readable",
545
+ "status": "passed",
546
+ "message": "Path is readable",
547
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
548
+ "details": {
549
+ "path": "/opt/sas/model-gli-text/models/medium/model.onnx"
550
+ },
551
+ "timestamp": 1777249827.3575964
552
+ },
553
+ {
554
+ "name": "File Type Validation",
555
+ "status": "passed",
556
+ "message": "File type validation passed",
557
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
558
+ "details": {},
559
+ "timestamp": 1777249827.3576233
560
+ },
561
+ {
562
+ "name": "File Integrity Hash",
563
+ "status": "passed",
564
+ "message": "File integrity hashes calculated",
565
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
566
+ "details": {
567
+ "md5": "67fab769e446bb64f1fc435a056bb656",
568
+ "sha256": "dfbf82b4c9b7cb8ebedb6e04bec068db7cfee3053cb90c7d4aa11b8a93edb46a",
569
+ "sha512": "4beeed401d13ff182de78ce3cc8829e45fba844b8952bdd7d4056c95fae5706216c57941b0793e7c51323af80d5d91ccf6f51ee8e2f9a2a2062ec1137cba6865",
570
+ "file_size": 835590772
571
+ },
572
+ "timestamp": 1777249831.6727397
573
+ },
574
+ {
575
+ "name": "JIT/Script Code Execution Detection",
576
+ "status": "passed",
577
+ "message": "No JIT/Script code execution risks detected",
578
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
579
+ "details": {},
580
+ "timestamp": 1777250298.1521664
581
+ },
582
+ {
583
+ "name": "Network Communication Detection",
584
+ "status": "passed",
585
+ "message": "No network communication patterns detected",
586
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
587
+ "details": {},
588
+ "timestamp": 1777250298.152354
589
+ },
590
+ {
591
+ "name": "Custom Operator Domain Check",
592
+ "status": "passed",
593
+ "message": "All operators use standard ONNX domains",
594
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
595
+ "details": {
596
+ "safe_nodes": 5171
597
+ },
598
+ "timestamp": 1777250298.1769123
599
+ },
600
+ {
601
+ "name": "Python Operator Detection",
602
+ "status": "passed",
603
+ "message": "No Python operators detected",
604
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
605
+ "details": {
606
+ "nodes_checked": 5171
607
+ },
608
+ "timestamp": 1777250298.1769633
609
+ },
610
+ {
611
+ "name": "Tensor Size Validation",
612
+ "status": "passed",
613
+ "message": "Tensor Size Validation completed successfully",
614
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx (tensor: core.token_rep_layer.bert_layer.model.embeddings.word_embeddings.weight)",
615
+ "details": {
616
+ "component_count": 217
617
+ },
618
+ "timestamp": 1777250299.9097366
619
+ },
620
+ {
621
+ "name": "Weight Distribution Analysis Coverage",
622
+ "status": "failed",
623
+ "message": "Weight distribution analysis skipped one or more eligible ONNX initializers",
624
+ "severity": "info",
625
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
626
+ "details": {
627
+ "scan_outcome_reason": "onnx_weight_distribution_analysis_incomplete",
628
+ "coverage_gap": "partial_initializer_coverage",
629
+ "eligible_initializers": 85,
630
+ "analyzed_initializers": 84,
631
+ "external_initializers_skipped": 0,
632
+ "oversized_initializers_skipped": 1,
633
+ "extraction_failures": 0,
634
+ "max_array_size": 104857600
635
+ },
636
+ "rule_code": "S902",
637
+ "timestamp": 1777250300.2641213
638
+ },
639
+ {
640
+ "name": "Weight Distribution Anomaly Detection",
641
+ "status": "failed",
642
+ "message": "Weight Distribution Anomaly Detection found 21 issues",
643
+ "severity": "info",
644
+ "location": "/opt/sas/model-gli-text/models/medium/model.onnx",
645
+ "details": {
646
+ "component_count": 21,
647
+ "findings": [
648
+ {
649
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
650
+ "neuron_index": 7,
651
+ "max_similarity_to_others": 0.6353273391723633,
652
+ "weight_norm": 5.372602462768555,
653
+ "total_outputs": 768,
654
+ "analysis_method": "structural_analysis"
655
+ },
656
+ {
657
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
658
+ "neuron_index": 48,
659
+ "max_similarity_to_others": 0.6696844100952148,
660
+ "weight_norm": 0.46152299642562866,
661
+ "total_outputs": 768,
662
+ "analysis_method": "structural_analysis"
663
+ },
664
+ {
665
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
666
+ "neuron_index": 117,
667
+ "max_similarity_to_others": 0.634371280670166,
668
+ "weight_norm": 0.39997434616088867,
669
+ "total_outputs": 768,
670
+ "analysis_method": "structural_analysis"
671
+ },
672
+ {
673
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
674
+ "neuron_index": 213,
675
+ "max_similarity_to_others": 0.6954333186149597,
676
+ "weight_norm": 0.5225619673728943,
677
+ "total_outputs": 768,
678
+ "analysis_method": "structural_analysis"
679
+ },
680
+ {
681
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
682
+ "neuron_index": 248,
683
+ "max_similarity_to_others": 0.6133643388748169,
684
+ "weight_norm": 0.47258928418159485,
685
+ "total_outputs": 768,
686
+ "analysis_method": "structural_analysis"
687
+ },
688
+ {
689
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
690
+ "neuron_index": 266,
691
+ "max_similarity_to_others": 0.649356484413147,
692
+ "weight_norm": 0.683588981628418,
693
+ "total_outputs": 768,
694
+ "analysis_method": "structural_analysis"
695
+ },
696
+ {
697
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
698
+ "neuron_index": 272,
699
+ "max_similarity_to_others": 0.6721497178077698,
700
+ "weight_norm": 0.4996761083602905,
701
+ "total_outputs": 768,
702
+ "analysis_method": "structural_analysis"
703
+ },
704
+ {
705
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
706
+ "neuron_index": 296,
707
+ "max_similarity_to_others": 0.6973440647125244,
708
+ "weight_norm": 0.5266340374946594,
709
+ "total_outputs": 768,
710
+ "analysis_method": "structural_analysis"
711
+ },
712
+ {
713
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
714
+ "neuron_index": 329,
715
+ "max_similarity_to_others": 0.6732807159423828,
716
+ "weight_norm": 0.7019028663635254,
717
+ "total_outputs": 768,
718
+ "analysis_method": "structural_analysis"
719
+ },
720
+ {
721
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
722
+ "neuron_index": 344,
723
+ "max_similarity_to_others": 0.5913342237472534,
724
+ "weight_norm": 1.2862828969955444,
725
+ "total_outputs": 768,
726
+ "analysis_method": "structural_analysis"
727
+ },
728
+ {
729
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
730
+ "neuron_index": 357,
731
+ "max_similarity_to_others": 0.6641792058944702,
732
+ "weight_norm": 0.5504754185676575,
733
+ "total_outputs": 768,
734
+ "analysis_method": "structural_analysis"
735
+ },
736
+ {
737
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
738
+ "neuron_index": 378,
739
+ "max_similarity_to_others": 0.5857805609703064,
740
+ "weight_norm": 0.5392732620239258,
741
+ "total_outputs": 768,
742
+ "analysis_method": "structural_analysis"
743
+ },
744
+ {
745
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
746
+ "neuron_index": 426,
747
+ "max_similarity_to_others": 0.6619596481323242,
748
+ "weight_norm": 0.4695207178592682,
749
+ "total_outputs": 768,
750
+ "analysis_method": "structural_analysis"
751
+ },
752
+ {
753
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
754
+ "neuron_index": 438,
755
+ "max_similarity_to_others": 0.6229392290115356,
756
+ "weight_norm": 0.43737903237342834,
757
+ "total_outputs": 768,
758
+ "analysis_method": "structural_analysis"
759
+ },
760
+ {
761
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
762
+ "neuron_index": 455,
763
+ "max_similarity_to_others": 0.6861489415168762,
764
+ "weight_norm": 0.500296413898468,
765
+ "total_outputs": 768,
766
+ "analysis_method": "structural_analysis"
767
+ },
768
+ {
769
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
770
+ "neuron_index": 481,
771
+ "max_similarity_to_others": 0.6357624530792236,
772
+ "weight_norm": 0.589555561542511,
773
+ "total_outputs": 768,
774
+ "analysis_method": "structural_analysis"
775
+ },
776
+ {
777
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
778
+ "neuron_index": 487,
779
+ "max_similarity_to_others": 0.6871294975280762,
780
+ "weight_norm": 0.47944051027297974,
781
+ "total_outputs": 768,
782
+ "analysis_method": "structural_analysis"
783
+ },
784
+ {
785
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
786
+ "neuron_index": 544,
787
+ "max_similarity_to_others": 0.6773201823234558,
788
+ "weight_norm": 0.5820121169090271,
789
+ "total_outputs": 768,
790
+ "analysis_method": "structural_analysis"
791
+ },
792
+ {
793
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
794
+ "neuron_index": 719,
795
+ "max_similarity_to_others": 0.6987954378128052,
796
+ "weight_norm": 0.7778415083885193,
797
+ "total_outputs": 768,
798
+ "analysis_method": "structural_analysis"
799
+ },
800
+ {
801
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
802
+ "neuron_index": 729,
803
+ "max_similarity_to_others": 0.6774657964706421,
804
+ "weight_norm": 0.6795850396156311,
805
+ "total_outputs": 768,
806
+ "analysis_method": "structural_analysis"
807
+ },
808
+ {
809
+ "layer": "core.token_rep_layer.bert_layer.model.encoder.rel_embeddings.weight",
810
+ "neuron_index": 739,
811
+ "max_similarity_to_others": 0.6594510674476624,
812
+ "weight_norm": 0.8022450804710388,
813
+ "total_outputs": 768,
814
+ "analysis_method": "structural_analysis"
815
+ }
816
+ ]
817
+ },
818
+ "why": "Neurons with weight patterns completely unlike others in the same layer are uncommon in standard training. This dissimilarity (measured by cosine similarity below threshold) may indicate injected functionality or training irregularities.",
819
+ "timestamp": 1777250303.197376
820
+ }
821
+ ],
822
+ "files_scanned": 6,
823
+ "assets": [
824
+ {
825
+ "path": "/opt/sas/model-gli-text/models/medium/README.md",
826
+ "type": "metadata",
827
+ "size": 1591
828
+ },
829
+ {
830
+ "path": "/opt/sas/model-gli-text/models/medium/gliner_config.json",
831
+ "type": "manifest",
832
+ "size": 2178,
833
+ "keys": [
834
+ "class_token_index",
835
+ "dropout",
836
+ "embed_ent_token",
837
+ "encoder_config",
838
+ "ent_token",
839
+ "fine_tune",
840
+ "fuse_layers",
841
+ "has_rnn",
842
+ "hidden_size",
843
+ "label_smoothing",
844
+ "loss_alpha",
845
+ "loss_gamma",
846
+ "loss_reduction",
847
+ "max_len",
848
+ "max_neg_type_ratio",
849
+ "max_types",
850
+ "max_width",
851
+ "model_name",
852
+ "model_type",
853
+ "name",
854
+ "neg_spans_ratio",
855
+ "num_post_fusion_layers",
856
+ "num_rnn_layers",
857
+ "post_fusion_schema",
858
+ "random_drop",
859
+ "represent_spans",
860
+ "sep_token",
861
+ "shuffle_types",
862
+ "span_loss_coef",
863
+ "span_mode",
864
+ "subtoken_pooling",
865
+ "token_loss_coef",
866
+ "transformers_version",
867
+ "vocab_size",
868
+ "words_splitter_type"
869
+ ]
870
+ },
871
+ {
872
+ "path": "/opt/sas/model-gli-text/models/medium/tokenizer_config.json",
873
+ "type": "jinja2_template",
874
+ "size": 502
875
+ },
876
+ {
877
+ "path": "/opt/sas/model-gli-text/models/medium/tokenizer.json",
878
+ "type": "jinja2_template",
879
+ "size": 8332739
880
+ },
881
+ {
882
+ "path": "/opt/sas/model-gli-text/models/medium/model.onnx",
883
+ "type": "onnx",
884
+ "size": 835590772
885
+ },
886
+ {
887
+ "path": "/opt/sas/model-gli-text/models/medium/LICENSE",
888
+ "type": "unknown"
889
+ }
890
+ ],
891
+ "has_errors": false,
892
+ "scanner_names": [
893
+ "metadata",
894
+ "manifest",
895
+ "jinja2_template",
896
+ "onnx"
897
+ ],
898
+ "file_metadata": {
899
+ "/opt/sas/model-gli-text/models/medium/README.md": {
900
+ "file_size": 1591,
901
+ "license_info": [
902
+ {
903
+ "spdx_id": "Apache-2.0",
904
+ "name": "Apache License 2.0",
905
+ "confidence": 0.8,
906
+ "source": "file_header",
907
+ "commercial_allowed": true
908
+ }
909
+ ],
910
+ "copyright_notices": [],
911
+ "license_files_nearby": [
912
+ "/opt/sas/model-gli-text/models/medium/LICENSE"
913
+ ],
914
+ "is_dataset": false,
915
+ "is_model": false,
916
+ "risk_score": 0.0,
917
+ "scan_timestamp": 1777249824.7508566,
918
+ "content_hash": "7999f932aa2777fb2d12a1e13ef146c5ce362bf185c600313c161d8f1618d4be"
919
+ },
920
+ "/opt/sas/model-gli-text/models/medium/gliner_config.json": {
921
+ "file_size": 2178,
922
+ "license_info": [],
923
+ "copyright_notices": [],
924
+ "license_files_nearby": [
925
+ "/opt/sas/model-gli-text/models/medium/LICENSE"
926
+ ],
927
+ "is_dataset": true,
928
+ "is_model": false,
929
+ "risk_score": 0.0,
930
+ "scan_timestamp": 1777249824.7844925,
931
+ "root_type": "dict",
932
+ "keys": [
933
+ "class_token_index",
934
+ "dropout",
935
+ "embed_ent_token",
936
+ "encoder_config",
937
+ "ent_token",
938
+ "fine_tune",
939
+ "fuse_layers",
940
+ "has_rnn",
941
+ "hidden_size",
942
+ "label_smoothing",
943
+ "loss_alpha",
944
+ "loss_gamma",
945
+ "loss_reduction",
946
+ "max_len",
947
+ "max_neg_type_ratio",
948
+ "max_types",
949
+ "max_width",
950
+ "model_name",
951
+ "model_type",
952
+ "name",
953
+ "neg_spans_ratio",
954
+ "num_post_fusion_layers",
955
+ "num_rnn_layers",
956
+ "post_fusion_schema",
957
+ "random_drop",
958
+ "represent_spans",
959
+ "sep_token",
960
+ "shuffle_types",
961
+ "span_loss_coef",
962
+ "span_mode",
963
+ "subtoken_pooling",
964
+ "token_loss_coef",
965
+ "transformers_version",
966
+ "vocab_size",
967
+ "words_splitter_type"
968
+ ],
969
+ "content_hash": "f538f4dc5ac579efed802ea637a413b8038d621f62f6acfb6f74e89eb7514be4"
970
+ },
971
+ "/opt/sas/model-gli-text/models/medium/tokenizer_config.json": {
972
+ "file_size": 502,
973
+ "ml_context": {
974
+ "frameworks": {},
975
+ "overall_confidence": 0.0,
976
+ "is_ml_content": false,
977
+ "detected_patterns": [],
978
+ "optimization_hints": [],
979
+ "file_type": "tokenizer_config",
980
+ "is_tokenizer": true,
981
+ "confidence": 2
982
+ },
983
+ "license_info": [],
984
+ "copyright_notices": [],
985
+ "license_files_nearby": [
986
+ "/opt/sas/model-gli-text/models/medium/LICENSE"
987
+ ],
988
+ "is_dataset": true,
989
+ "is_model": false,
990
+ "risk_score": 0.0,
991
+ "scan_timestamp": 1777249824.836328,
992
+ "content_hash": "818c97fbc7f072800ccc379fd72e1e1b2506d30d7fd5bee8a5e4c8bd61bd805c"
993
+ },
994
+ "/opt/sas/model-gli-text/models/medium/tokenizer.json": {
995
+ "file_size": 8332739,
996
+ "ml_context": {
997
+ "frameworks": {},
998
+ "overall_confidence": 0.0,
999
+ "is_ml_content": false,
1000
+ "detected_patterns": [],
1001
+ "optimization_hints": [],
1002
+ "file_type": "tokenizer_config",
1003
+ "is_tokenizer": true,
1004
+ "confidence": 2
1005
+ },
1006
+ "license_info": [],
1007
+ "copyright_notices": [],
1008
+ "license_files_nearby": [
1009
+ "/opt/sas/model-gli-text/models/medium/LICENSE"
1010
+ ],
1011
+ "is_dataset": true,
1012
+ "is_model": false,
1013
+ "risk_score": 0.0,
1014
+ "scan_timestamp": 1777249827.3364515,
1015
+ "content_hash": "08bb5853718f4a829fa9ce773d7984f7f3f6a7073fdc82a07a382675c5061ba6"
1016
+ },
1017
+ "/opt/sas/model-gli-text/models/medium/model.onnx": {
1018
+ "file_size": 835590772,
1019
+ "file_hashes": {
1020
+ "md5": "67fab769e446bb64f1fc435a056bb656",
1021
+ "sha256": "dfbf82b4c9b7cb8ebedb6e04bec068db7cfee3053cb90c7d4aa11b8a93edb46a",
1022
+ "sha512": "4beeed401d13ff182de78ce3cc8829e45fba844b8952bdd7d4056c95fae5706216c57941b0793e7c51323af80d5d91ccf6f51ee8e2f9a2a2062ec1137cba6865"
1023
+ },
1024
+ "license_info": [],
1025
+ "copyright_notices": [],
1026
+ "license_files_nearby": [
1027
+ "/opt/sas/model-gli-text/models/medium/LICENSE"
1028
+ ],
1029
+ "is_dataset": false,
1030
+ "is_model": true,
1031
+ "risk_score": 0.0,
1032
+ "scan_timestamp": 1777250303.7373185,
1033
+ "ir_version": 7,
1034
+ "producer_name": "pytorch",
1035
+ "node_count": 5171,
1036
+ "scan_outcome": "inconclusive",
1037
+ "scan_outcome_reasons": [
1038
+ "onnx_weight_distribution_analysis_incomplete"
1039
+ ],
1040
+ "layers_analyzed": 84,
1041
+ "anomalies_found": 21,
1042
+ "content_hash": "dfbf82b4c9b7cb8ebedb6e04bec068db7cfee3053cb90c7d4aa11b8a93edb46a"
1043
+ },
1044
+ "/opt/sas/model-gli-text/models/medium/LICENSE": {
1045
+ "license_info": [
1046
+ {
1047
+ "spdx_id": "Apache-2.0",
1048
+ "name": "Apache License 2.0",
1049
+ "confidence": 0.8,
1050
+ "source": "file_header",
1051
+ "commercial_allowed": true
1052
+ }
1053
+ ],
1054
+ "copyright_notices": [],
1055
+ "license_files_nearby": [
1056
+ "/opt/sas/model-gli-text/models/medium/LICENSE"
1057
+ ],
1058
+ "is_dataset": false,
1059
+ "is_model": false,
1060
+ "risk_score": 0.0,
1061
+ "scan_timestamp": 1777250303.7449977,
1062
+ "content_hash": "cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30"
1063
+ }
1064
+ },
1065
+ "content_hash": "8f06b3046d0d86ac35db3b5469e20a6e85aeb41b5b2e384e97535b79a654d23c",
1066
+ "start_time": 1777249823.545908,
1067
+ "duration": 480.208021402359,
1068
+ "total_checks": 24,
1069
+ "passed_checks": 24,
1070
+ "failed_checks": 0,
1071
+ "success": false
1072
+ }
1073
+ }