rpeel commited on
Commit
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Update model card and security scan results

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Files changed (2) hide show
  1. README.md +38 -7
  2. modelaudit.json +889 -0
README.md CHANGED
@@ -1,22 +1,53 @@
1
  ---
2
  library_name: glitext
 
3
  tags:
4
- - glitext
5
  glitext:
6
- name: "multitask-v0.5"
7
- label: "GliText Multitask (Fast)"
8
- description: "An efficient zero-shot entity relation association model tuned for high throughput (speed)."
9
  recognition: true
10
  classification: true
11
  association: true
12
  span_mode: true
13
  size_gb: 1.77
14
- hf_repo: "rpeel/glitext-multitask-v0.5"
15
- source_url: "knowledgator/gliner-multitask-large-v0.5"
16
  ---
17
 
18
  # rpeel/glitext-multitask-v0.5
19
 
20
  An efficient zero-shot entity relation association model tuned for high throughput (speed).
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: multitask-v0.5
8
+ label: GliText Multitask (Fast)
9
+ description: An efficient zero-shot entity relation association model tuned for high throughput (speed).
10
  recognition: true
11
  classification: true
12
  association: true
13
  span_mode: true
14
  size_gb: 1.77
15
+ hf_repo: rpeel/glitext-multitask-v0.5
16
+ source_url: knowledgator/gliner-multitask-large-v0.5
17
  ---
18
 
19
  # rpeel/glitext-multitask-v0.5
20
 
21
  An efficient zero-shot entity relation association model tuned for high throughput (speed).
22
 
23
+ ## Requirements
24
+
25
+ To download this model to the SAS GLiText server:
26
+
27
+ ```
28
+ POST /v1/models/download?name=multitask-v0.5
29
+ ```
30
+
31
+ To download and load into memory in one step:
32
+
33
+ ```
34
+ PUT /v1/models?name=multitask-v0.5
35
+ ```
36
+
37
+ ## Source Model
38
+
39
+ Exported from [knowledgator/gliner-multitask-large-v0.5](https://huggingface.co/knowledgator/gliner-multitask-large-v0.5).
40
+ See the [original model card](https://huggingface.co/knowledgator/gliner-multitask-large-v0.5) 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. 32/32 checks passed. [Full results](modelaudit.json).
45
+
46
+
47
+ | File | Size | SHA-256 |
48
+ |------|------|---------|
49
+ | `model.onnx` | 1763.5 MB | `9f96655e9758dd44…` |
50
+
51
+ ## License
52
+
53
+ [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0). Derived from [knowledgator/gliner-multitask-large-v0.5](https://huggingface.co/knowledgator/gliner-multitask-large-v0.5) by [knowledgator](https://huggingface.co/knowledgator).
modelaudit.json ADDED
@@ -0,0 +1,889 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "tool": "modelaudit",
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+ "tool_version": "0.2.40",
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+ "scanned_at": "2026-04-27T01:14:00Z",
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+ "files": {
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+ "model.onnx": {
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+ "size_mb": 1763.5,
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+ "sha256": "9f96655e9758dd4476bfda380e33fdd03995fa353b18e251a608ce78f6e9453d"
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+ "message": "Weight distribution analysis skipped one or more eligible ONNX initializers",
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+ "severity": "info",
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+ "location": "/opt/sas/model-gli-text/models/multitask-v0.5/model.onnx",
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+ "details": {
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+ "scan_outcome_reason": "onnx_weight_distribution_analysis_incomplete",
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+ "coverage_gap": "partial_initializer_coverage",
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+ "eligible_initializers": 154,
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+ "analyzed_initializers": 153,
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+ "external_initializers_skipped": 0,
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+ "oversized_initializers_skipped": 1,
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+ "extraction_failures": 0,
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+ "max_array_size": 104857600
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+ "timestamp": 1777252430.569848,
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+ "type": "onnx_check",
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+ "rule_code": "S902"
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+ },
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+ {
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+ "message": "Layer 'onnx::MatMul_12848' output neuron 0 has unusually dissimilar weights",
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+ "severity": "info",
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+ "location": "/opt/sas/model-gli-text/models/multitask-v0.5/model.onnx",
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+ "details": {
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+ "layer": "onnx::MatMul_12848",
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+ "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.",
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+ "timestamp": 1777252435.7678933,
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+ "type": "onnx_check",
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+ "rule_code": "S803"
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+ },
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+ {
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+ "message": "Layer 'onnx::MatMul_12848' output neuron 1 has unusually dissimilar weights",
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+ "severity": "info",
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+ "location": "/opt/sas/model-gli-text/models/multitask-v0.5/model.onnx",
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+ "details": {
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+ "analysis_method": "structural_analysis"
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+ },
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+ "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.",
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+ "timestamp": 1777252435.7684815,
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+ "type": "onnx_check",
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+ "rule_code": "S803"
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+ },
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+ {
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+ "message": "Layer 'onnx::MatMul_12848' output neuron 2 has unusually dissimilar weights",
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+ "severity": "info",
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+ "location": "/opt/sas/model-gli-text/models/multitask-v0.5/model.onnx",
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+ "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.",
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+ "timestamp": 1777252435.768858,
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+ "type": "onnx_check",
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+ "rule_code": "S803"
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+ },
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+ {
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+ "message": "Layer 'onnx::MatMul_12848' has neurons with extremely large weight values",
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+ "severity": "info",
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+ "location": "/opt/sas/model-gli-text/models/multitask-v0.5/model.onnx",
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+ "details": {
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+ },
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+ "why": "Weight values that are orders of magnitude larger than typical can cause numerical instability, overflow attacks, or may encode hidden data. Detection uses statistical analysis rather than name-based classification to avoid security bypasses.",
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+ "timestamp": 1777252435.7691994,
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+ "type": "onnx_check",
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+ "rule_code": "S802"
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+ {
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+ "message": "File does not contain expected XGBoost binary model markers",
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+ "severity": "info",
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+ "reg:",
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+ "timestamp": 1777252436.8859515,
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+ "type": "xgboost_check"
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+ "name": "Path Exists",
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+ "status": "passed",
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+ "message": "Path exists",
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+ "name": "File Type Validation",
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+ "name": "Path Readable",
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+ "severity": "info",
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+ "status": "failed",
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+ "message": "Weight Distribution Anomaly Detection found 4 issues",
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