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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,126 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: gemma
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+ language:
4
+ - en
5
+ base_model: google/gemma-4-26b-a4b-it
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+ tags:
7
+ - mlx
8
+ - mlx-node
9
+ - quantized
10
+ - awq
11
+ - gemma4
12
+ - moe
13
+ - sliding-window-attention
14
+ - vision-language
15
+ - apple-silicon
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+ - unsloth-dynamic
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+ library_name: mlx-node
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+ quantized_by: mlx-node
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+ pipeline_tag: text-generation
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+ model_type: gemma4
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+ ---
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+
23
+ # Gemma-4-26B-A4B-IT — UD-Q5_K_XL (mlx-node)
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+
25
+ 5-bit affine quantization of [google/gemma-4-26b-a4b-it](https://huggingface.co/google/gemma-4-26b-a4b-it) for Apple Silicon, using the [**Unsloth Dynamic** quantization strategy](https://unsloth.ai/docs/models/qwen3.5/gguf-benchmarks) via [mlx-node](https://github.com/mlx-node/mlx-node).
26
+
27
+ | | Original (BF16) | UD-Q5_K_XL (this model) |
28
+ |---|---|---|
29
+ | **Size** | ~49 GB | **20 GB** |
30
+ | **Format** | SafeTensors | SafeTensors |
31
+ | **Precision** | BF16 uniform | 5-bit affine + mixed bits + BF16 |
32
+ | **FFN group size** | — | **64** |
33
+ | **Biases** | — | yes |
34
+
35
+ ## All Variants
36
+
37
+ | Repo | Bit budget | Size | Decode (tok/s) |
38
+ |---|---|---|---|
39
+ | [Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q3_K_XL-mlx](https://huggingface.co/Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q3_K_XL-mlx) | 3-bit base | 14 GB | 60.6 |
40
+ | [Brooooooklyn/Gemma-4-26B-A4B-IT-UD-MXFP4_K_XL-mlx](https://huggingface.co/Brooooooklyn/Gemma-4-26B-A4B-IT-UD-MXFP4_K_XL-mlx) | mxfp4 | 16 GB | 58.4 |
41
+ | [Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q4_K_XL-mlx](https://huggingface.co/Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q4_K_XL-mlx) | 4-bit base | 17 GB | 58.6 |
42
+ | [Brooooooklyn/Gemma-4-26B-A4B-IT-UD-NVFP4_K_XL-mlx](https://huggingface.co/Brooooooklyn/Gemma-4-26B-A4B-IT-UD-NVFP4_K_XL-mlx) | nvfp4 | 17 GB | 57.9 |
43
+ | **[Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q5_K_XL-mlx](https://huggingface.co/Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q5_K_XL-mlx) (this model)** | **5-bit base** | **20 GB** | **50.3** |
44
+ | [Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q6_K_XL-mlx](https://huggingface.co/Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q6_K_XL-mlx) | 6-bit base | 23 GB | 51.9 |
45
+ | [Brooooooklyn/Gemma-4-26B-A4B-IT-UD-MXFP8_K_XL-mlx](https://huggingface.co/Brooooooklyn/Gemma-4-26B-A4B-IT-UD-MXFP8_K_XL-mlx) | mxfp8 | 26 GB | 49.8 |
46
+ | [Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q8_K_XL-mlx](https://huggingface.co/Brooooooklyn/Gemma-4-26B-A4B-IT-UD-Q8_K_XL-mlx) | 8-bit base | 27 GB | 49.8 |
47
+
48
+ Benchmarked on Apple M3 Max 128GB via [`examples/lm.ts`](https://github.com/mlx-node/mlx-node/blob/main/examples/lm.ts) (best decode tok/s across turns 2–4, steady-state, capitals chat with `reasoningEffort: 'low'`).
49
+
50
+ **Note:** No Q2 variant is published — Gemma-4-26B-A4B-IT has only ~4B active parameters per token, which is below the architectural redundancy needed for 2-bit quantization to remain coherent. Both `unsloth` and `mixed_2_6` recipes produced gibberish at Q2 on this model.
51
+
52
+ ## Performance
53
+
54
+ Steady-state decode: **50.3 tok/s** on Apple M3 Max 128GB (best of turns 2–4, `examples/lm.ts` capitals chat with `reasoningEffort: 'low'`). Decode is memory-bandwidth bound on Apple Silicon — fewer bytes per token directly translates to higher throughput. The MoE architecture activates only top-K of 128 experts per token (~4B active out of ~26B total), and the compiled C++ forward graph fuses the per-layer dispatch.
55
+
56
+ ## Per-Tensor Bit Assignments (N=5)
57
+
58
+ | Weight | Mode | Bits | Group | Rationale |
59
+ |---|---|---|---|---|
60
+ | `embed_tokens` | 8-bit affine | 8 | 64 | Tied with lm_head (Gemma4 shares weights); affine-only loader |
61
+ | `self_attn.q_proj` | 8-bit affine | 8 | 64 | AWQ-corrected via input_layernorm |
62
+ | `self_attn.k_proj` | 8-bit affine | 8 | 64 | AWQ-corrected via input_layernorm |
63
+ | `self_attn.v_proj` | 8-bit affine | 8 | 64 | AWQ-corrected via input_layernorm (only on full-attention layers) |
64
+ | `mlp.gate_proj` | 5-bit affine | 5 | 64 | Shared dense MLP (top-level default) |
65
+ | `mlp.up_proj` | 5-bit affine | 5 | 64 | Shared dense MLP (top-level default) |
66
+ | `mlp.down_proj` | 6-bit affine | 6 | 64 | Shared dense MLP; "slightly more sensitive" (unsloth `base+1`) |
67
+ | `experts.switch_glu.gate_proj` | 5-bit affine | 5 | 64 | MoE expert gate (per-expert across all 128); base bits (top-level default) |
68
+ | `experts.switch_glu.up_proj` | 5-bit affine | 5 | 64 | MoE expert up (per-expert across all 128); base bits (top-level default) |
69
+ | `experts.switch_glu.down_proj` | 6-bit affine | 6 | 64 | MoE expert down (per-expert across all 128 + routing); unsloth `base+1` |
70
+ | `router.proj` | 8-bit affine | 8 | 64 | MoE routing — low-bit noise breaks top-K expert selection |
71
+ | `self_attn.o_proj` | **bf16** | — | — | NOT AWQ-correctable; kept full-precision |
72
+
73
+ ## Quantization Strategy
74
+
75
+ Built on Unsloth Dynamic 2.0 per-tensor KLD analysis. At `--q-bits 5` the unsloth recipe assigns the base bits to MLP gate/up projections (the bulk of the parameter budget), `base+1` to down_proj (slightly more sensitive), `base+2` (snapped to a valid bit width) + AWQ pre-scaling to attention q/k/v projections, `base+2` to `embed_tokens`, `base+3` (capped/snapped) to the routing-critical paths, and keeps `self_attn.o_proj` as bf16 (AWQ-uncorrectable — its inputs come from the attention compute, not from a norm layer). The MoE router (`router.proj`) is forced to 8-bit affine to preserve top-K expert selection accuracy.
76
+
77
+ imatrix AWQ pre-scaling amplifies important weight channels and fuses inverse scales into preceding layer norms (zero inference overhead).
78
+
79
+ ## Architecture
80
+
81
+ | Parameter | Value |
82
+ |---|---|
83
+ | Total parameters | ~26B (~4B active per token) |
84
+ | Hidden size | 2,816 |
85
+ | Layers | 30 (sliding-window attention) |
86
+ | Attention heads | 16 (8 KV heads, GQA 2:1) |
87
+ | Head dimension | 256 |
88
+ | Experts | 128 per MoE layer |
89
+ | MoE intermediate size | 704 |
90
+ | Vocab size | 262,144 |
91
+ | Max context | 262,144 tokens |
92
+ | Vision | yes (Gemma4ForConditionalGeneration) |
93
+
94
+ ## Usage
95
+
96
+ ```typescript
97
+ import { loadSession } from '@mlx-node/lm';
98
+
99
+ const session = await loadSession('./Gemma-4-26B-A4B-IT-UD-Q5_K_XL-mlx');
100
+
101
+ for await (const event of session.sendStream('Explain the MoE architecture in Gemma-4.', {
102
+ config: { maxNewTokens: 2048, temperature: 0.6, reasoningEffort: 'low' },
103
+ })) {
104
+ if (!event.done) process.stdout.write(event.text);
105
+ }
106
+ ```
107
+
108
+ ## How It Was Made
109
+
110
+ ```bash
111
+ mlx convert \
112
+ -i gemma-4-26b-a4b-it \
113
+ -o Gemma-4-26B-A4B-IT-UD-Q5_K_XL-mlx \
114
+ -q --q-bits 5 --q-recipe unsloth \
115
+ --imatrix-path imatrix_unsloth.gguf
116
+ ```
117
+
118
+ ## Acknowledgments
119
+
120
+ - **[Unsloth](https://unsloth.ai)** — Quantization strategy based on their [per-layer KLD benchmarks](https://unsloth.ai/docs/models/qwen3.5/gguf-benchmarks) and Dynamic 2.0 methodology
121
+ - **[Google DeepMind](https://deepmind.google/)** — For the Gemma-4 model family
122
+ - **[Apple MLX](https://github.com/ml-explore/mlx)** — For the Metal-accelerated ML framework
123
+
124
+ ## License
125
+
126
+ [Gemma Terms of Use](https://ai.google.dev/gemma/terms) (inherited from base model).
chat_template.jinja ADDED
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1
+ {%- macro format_parameters(properties, required, filter_keys=false) -%}
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+ {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}
3
+ {%- set ns = namespace(found_first=false) -%}
4
+ {%- for key, value in properties | dictsort -%}
5
+ {%- set add_comma = false -%}
6
+ {%- if not filter_keys or key not in standard_keys -%}
7
+ {%- if ns.found_first %},{% endif -%}
8
+ {%- set ns.found_first = true -%}
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+ {{ key }}:{
10
+ {%- if value['description'] -%}
11
+ description:<|"|>{{ value['description'] }}<|"|>
12
+ {%- set add_comma = true -%}
13
+ {%- endif -%}
14
+ {%- if value['type'] | upper == 'STRING' -%}
15
+ {%- if value['enum'] -%}
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+ {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
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+ enum:{{ format_argument(value['enum']) }}
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+ {%- endif -%}
19
+ {%- elif value['type'] | upper == 'ARRAY' -%}
20
+ {%- if value['items'] is mapping and value['items'] -%}
21
+ {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
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+ items:{
23
+ {%- set ns_items = namespace(found_first=false) -%}
24
+ {%- for item_key, item_value in value['items'] | dictsort -%}
25
+ {%- if item_value is not none -%}
26
+ {%- if ns_items.found_first %},{% endif -%}
27
+ {%- set ns_items.found_first = true -%}
28
+ {%- if item_key == 'properties' -%}
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+ properties:{
30
+ {%- if item_value is mapping -%}
31
+ {{- format_parameters(item_value, value['items']['required'] | default([])) -}}
32
+ {%- endif -%}
33
+ }
34
+ {%- elif item_key == 'required' -%}
35
+ required:[
36
+ {%- for req_item in item_value -%}
37
+ <|"|>{{- req_item -}}<|"|>
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+ {%- if not loop.last %},{% endif -%}
39
+ {%- endfor -%}
40
+ ]
41
+ {%- elif item_key == 'type' -%}
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+ {%- if item_value is string -%}
43
+ type:{{ format_argument(item_value | upper) }}
44
+ {%- else -%}
45
+ type:{{ format_argument(item_value | map('upper') | list) }}
46
+ {%- endif -%}
47
+ {%- else -%}
48
+ {{ item_key }}:{{ format_argument(item_value) }}
49
+ {%- endif -%}
50
+ {%- endif -%}
51
+ {%- endfor -%}
52
+ }
53
+ {%- endif -%}
54
+ {%- endif -%}
55
+ {%- if value['nullable'] %}
56
+ {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
57
+ nullable:true
58
+ {%- endif -%}
59
+ {%- if value['type'] | upper == 'OBJECT' -%}
60
+ {%- if value['properties'] is defined and value['properties'] is mapping -%}
61
+ {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
62
+ properties:{
63
+ {{- format_parameters(value['properties'], value['required'] | default([])) -}}
64
+ }
65
+ {%- elif value is mapping -%}
66
+ {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
67
+ properties:{
68
+ {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}
69
+ }
70
+ {%- endif -%}
71
+ {%- if value['required'] -%}
72
+ {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
73
+ required:[
74
+ {%- for item in value['required'] | default([]) -%}
75
+ <|"|>{{- item -}}<|"|>
76
+ {%- if not loop.last %},{% endif -%}
77
+ {%- endfor -%}
78
+ ]
79
+ {%- endif -%}
80
+ {%- endif -%}
81
+ {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
82
+ type:<|"|>{{ value['type'] | upper }}<|"|>}
83
+ {%- endif -%}
84
+ {%- endfor -%}
85
+ {%- endmacro -%}
86
+ {%- macro format_function_declaration(tool_data) -%}
87
+ declaration:{{- tool_data['function']['name'] -}}{description:<|"|>{{- tool_data['function']['description'] -}}<|"|>
88
+ {%- set params = tool_data['function']['parameters'] -%}
89
+ {%- if params -%}
90
+ ,parameters:{
91
+ {%- if params['properties'] -%}
92
+ properties:{ {{- format_parameters(params['properties'], params['required']) -}} },
93
+ {%- endif -%}
94
+ {%- if params['required'] -%}
95
+ required:[
96
+ {%- for item in params['required'] -%}
97
+ <|"|>{{- item -}}<|"|>
98
+ {{- ',' if not loop.last -}}
99
+ {%- endfor -%}
100
+ ],
101
+ {%- endif -%}
102
+ {%- if params['type'] -%}
103
+ type:<|"|>{{- params['type'] | upper -}}<|"|>}
104
+ {%- endif -%}
105
+ {%- endif -%}
106
+ {%- if 'response' in tool_data['function'] -%}
107
+ {%- set response_declaration = tool_data['function']['response'] -%}
108
+ ,response:{
109
+ {%- if response_declaration['description'] -%}
110
+ description:<|"|>{{- response_declaration['description'] -}}<|"|>,
111
+ {%- endif -%}
112
+ {%- if response_declaration['type'] | upper == 'OBJECT' -%}
113
+ type:<|"|>{{- response_declaration['type'] | upper -}}<|"|>}
114
+ {%- endif -%}
115
+ {%- endif -%}
116
+ }
117
+ {%- endmacro -%}
118
+ {%- macro format_argument(argument, escape_keys=True) -%}
119
+ {%- if argument is string -%}
120
+ {{- '<|"|>' + argument + '<|"|>' -}}
121
+ {%- elif argument is boolean -%}
122
+ {{- 'true' if argument else 'false' -}}
123
+ {%- elif argument is mapping -%}
124
+ {{- '{' -}}
125
+ {%- set ns = namespace(found_first=false) -%}
126
+ {%- for key, value in argument | dictsort -%}
127
+ {%- if ns.found_first %},{% endif -%}
128
+ {%- set ns.found_first = true -%}
129
+ {%- if escape_keys -%}
130
+ {{- '<|"|>' + key + '<|"|>' -}}
131
+ {%- else -%}
132
+ {{- key -}}
133
+ {%- endif -%}
134
+ :{{- format_argument(value, escape_keys=escape_keys) -}}
135
+ {%- endfor -%}
136
+ {{- '}' -}}
137
+ {%- elif argument is sequence -%}
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+ {{- '[' -}}
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+ {%- for item in argument -%}
140
+ {{- format_argument(item, escape_keys=escape_keys) -}}
141
+ {%- if not loop.last %},{% endif -%}
142
+ {%- endfor -%}
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+ {{- ']' -}}
144
+ {%- else -%}
145
+ {{- argument -}}
146
+ {%- endif -%}
147
+ {%- endmacro -%}
148
+ {%- macro strip_thinking(text) -%}
149
+ {%- set ns = namespace(result='') -%}
150
+ {%- for part in text.split('<channel|>') -%}
151
+ {%- if '<|channel>' in part -%}
152
+ {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}
153
+ {%- else -%}
154
+ {%- set ns.result = ns.result + part -%}
155
+ {%- endif -%}
156
+ {%- endfor -%}
157
+ {{- ns.result | trim -}}
158
+ {%- endmacro -%}
159
+
160
+ {%- macro format_tool_response_block(tool_name, response) -%}
161
+ {{- '<|tool_response>' -}}
162
+ {%- if response is mapping -%}
163
+ {{- 'response:' + tool_name + '{' -}}
164
+ {%- for key, value in response | dictsort -%}
165
+ {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
166
+ {%- if not loop.last %},{% endif -%}
167
+ {%- endfor -%}
168
+ {{- '}' -}}
169
+ {%- else -%}
170
+ {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}
171
+ {%- endif -%}
172
+ {{- '<tool_response|>' -}}
173
+ {%- endmacro -%}
174
+
175
+ {%- set ns = namespace(prev_message_type=None) -%}
176
+ {%- set loop_messages = messages -%}
177
+ {{- bos_token -}}
178
+ {#- Handle System/Tool Definitions Block -#}
179
+ {%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}
180
+ {{- '<|turn>system\n' -}}
181
+ {#- Inject Thinking token at the very top of the FIRST system turn -#}
182
+ {%- if enable_thinking is defined and enable_thinking -%}
183
+ {{- '<|think|>\n' -}}
184
+ {%- set ns.prev_message_type = 'think' -%}
185
+ {%- endif -%}
186
+ {%- if messages[0]['role'] in ['system', 'developer'] -%}
187
+ {%- if messages[0]['content'] is string -%}
188
+ {{- messages[0]['content'] | trim -}}
189
+ {%- elif messages[0]['content'] is sequence -%}
190
+ {%- for item in messages[0]['content'] -%}
191
+ {{- item['text'] | trim + ' '-}}
192
+ {%- endfor -%}
193
+ {%- endif -%}
194
+ {%- set loop_messages = messages[1:] -%}
195
+ {%- endif -%}
196
+ {%- if tools -%}
197
+ {%- for tool in tools %}
198
+ {{- '<|tool>' -}}
199
+ {{- format_function_declaration(tool) | trim -}}
200
+ {{- '<tool|>' -}}
201
+ {%- endfor %}
202
+ {%- set ns.prev_message_type = 'tool' -%}
203
+ {%- endif -%}
204
+ {{- '<turn|>\n' -}}
205
+ {%- endif %}
206
+
207
+ {#- Pre-scan: find last user message index for reasoning guard -#}
208
+ {%- set ns_turn = namespace(last_user_idx=-1) -%}
209
+ {%- for i in range(loop_messages | length) -%}
210
+ {%- if loop_messages[i]['role'] == 'user' -%}
211
+ {%- set ns_turn.last_user_idx = i -%}
212
+ {%- endif -%}
213
+ {%- endfor -%}
214
+
215
+ {#- Loop through messages -#}
216
+ {%- for message in loop_messages -%}
217
+ {%- if message['role'] != 'tool' -%}
218
+ {%- set ns.prev_message_type = None -%}
219
+ {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}
220
+ {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}
221
+ {%- set prev_nt = namespace(role=None, found=false) -%}
222
+ {%- if loop.index0 > 0 -%}
223
+ {%- for j in range(loop.index0 - 1, -1, -1) -%}
224
+ {%- if not prev_nt.found -%}
225
+ {%- if loop_messages[j]['role'] != 'tool' -%}
226
+ {%- set prev_nt.role = loop_messages[j]['role'] -%}
227
+ {%- set prev_nt.found = true -%}
228
+ {%- endif -%}
229
+ {%- endif -%}
230
+ {%- endfor -%}
231
+ {%- endif -%}
232
+ {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}
233
+ {%- if not continue_same_model_turn -%}
234
+ {{- '<|turn>' + role + '\n' }}
235
+ {%- endif -%}
236
+
237
+ {#- Render reasoning/reasoning_content as thinking channel -#}
238
+ {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}
239
+ {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}
240
+ {{- '<|channel>thought\n' + thinking_text + '\n<channel|>' -}}
241
+ {%- endif -%}
242
+
243
+ {%- if message['tool_calls'] -%}
244
+ {%- for tool_call in message['tool_calls'] -%}
245
+ {%- set function = tool_call['function'] -%}
246
+ {{- '<|tool_call>call:' + function['name'] + '{' -}}
247
+ {%- if function['arguments'] is mapping -%}
248
+ {%- set ns_args = namespace(found_first=false) -%}
249
+ {%- for key, value in function['arguments'] | dictsort -%}
250
+ {%- if ns_args.found_first %},{% endif -%}
251
+ {%- set ns_args.found_first = true -%}
252
+ {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
253
+ {%- endfor -%}
254
+ {%- elif function['arguments'] is string -%}
255
+ {{- function['arguments'] -}}
256
+ {%- endif -%}
257
+ {{- '}<tool_call|>' -}}
258
+ {%- endfor -%}
259
+ {%- set ns.prev_message_type = 'tool_call' -%}
260
+ {%- endif -%}
261
+
262
+ {%- set ns_tr_out = namespace(flag=false) -%}
263
+ {%- if message.get('tool_responses') -%}
264
+ {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}
265
+ {%- for tool_response in message['tool_responses'] -%}
266
+ {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}
267
+ {%- set ns_tr_out.flag = true -%}
268
+ {%- set ns.prev_message_type = 'tool_response' -%}
269
+ {%- endfor -%}
270
+ {%- elif message.get('tool_calls') -%}
271
+ {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}
272
+ {%- set ns_tool_scan = namespace(stopped=false) -%}
273
+ {%- for k in range(loop.index0 + 1, loop_messages | length) -%}
274
+ {%- if ns_tool_scan.stopped -%}
275
+ {%- elif loop_messages[k]['role'] != 'tool' -%}
276
+ {%- set ns_tool_scan.stopped = true -%}
277
+ {%- else -%}
278
+ {%- set follow = loop_messages[k] -%}
279
+ {#- Resolve tool_call_id to function name -#}
280
+ {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}
281
+ {%- for tc in message['tool_calls'] -%}
282
+ {%- if tc.get('id') == follow.get('tool_call_id') -%}
283
+ {%- set ns_tname.name = tc['function']['name'] -%}
284
+ {%- endif -%}
285
+ {%- endfor -%}
286
+ {#- Handle content as string or content-parts array -#}
287
+ {%- set tool_body = follow.get('content') -%}
288
+ {%- if tool_body is string -%}
289
+ {{- format_tool_response_block(ns_tname.name, tool_body) -}}
290
+ {%- elif tool_body is sequence and tool_body is not string -%}
291
+ {%- set ns_txt = namespace(s='') -%}
292
+ {%- for part in tool_body -%}
293
+ {%- if part.get('type') == 'text' -%}
294
+ {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}
295
+ {%- endif -%}
296
+ {%- endfor -%}
297
+ {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}
298
+ {%- else -%}
299
+ {{- format_tool_response_block(ns_tname.name, tool_body) -}}
300
+ {%- endif -%}
301
+ {%- set ns_tr_out.flag = true -%}
302
+ {%- set ns.prev_message_type = 'tool_response' -%}
303
+ {%- endif -%}
304
+ {%- endfor -%}
305
+ {%- endif -%}
306
+
307
+ {%- set captured_content -%}
308
+ {%- if message['content'] is string -%}
309
+ {%- if role == 'model' -%}
310
+ {{- strip_thinking(message['content']) -}}
311
+ {%- else -%}
312
+ {{- message['content'] | trim -}}
313
+ {%- endif -%}
314
+ {%- elif message['content'] is sequence -%}
315
+ {%- for item in message['content'] -%}
316
+ {%- if item['type'] == 'text' -%}
317
+ {%- if role == 'model' -%}
318
+ {{- strip_thinking(item['text']) -}}
319
+ {%- else -%}
320
+ {{- item['text'] | trim -}}
321
+ {%- endif -%}
322
+ {%- elif item['type'] == 'image' -%}
323
+ {{- '<|image|>' -}}
324
+ {%- set ns.prev_message_type = 'image' -%}
325
+ {%- elif item['type'] == 'audio' -%}
326
+ {{- '<|audio|>' -}}
327
+ {%- set ns.prev_message_type = 'audio' -%}
328
+ {%- elif item['type'] == 'video' -%}
329
+ {{- '<|video|>' -}}
330
+ {%- set ns.prev_message_type = 'video' -%}
331
+ {%- endif -%}
332
+ {%- endfor -%}
333
+ {%- endif -%}
334
+ {%- endset -%}
335
+
336
+ {{- captured_content -}}
337
+ {%- set has_content = captured_content | trim | length > 0 -%}
338
+
339
+ {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}
340
+ {{- '<|tool_response>' -}}
341
+ {%- elif not (ns_tr_out.flag and not has_content) -%}
342
+ {{- '<turn|>\n' -}}
343
+ {%- endif -%}
344
+ {%- endif -%}
345
+ {%- endfor -%}
346
+
347
+ {%- if add_generation_prompt -%}
348
+ {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}
349
+ {{- '<|turn>model\n' -}}
350
+ {%- if not enable_thinking | default(false) -%}
351
+ {{- '<|channel>thought\n<channel|>' -}}
352
+ {%- endif -%}
353
+ {%- endif -%}
354
+ {%- endif -%}
config.json ADDED
@@ -0,0 +1,1916 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "Gemma4ForConditionalGeneration"
4
+ ],
5
+ "audio_config": null,
6
+ "audio_token_id": 258881,
7
+ "boa_token_id": 256000,
8
+ "boi_token_id": 255999,
9
+ "dtype": "bfloat16",
10
+ "eoa_token_id": 258883,
11
+ "eoa_token_index": 258883,
12
+ "eoi_token_id": 258882,
13
+ "eos_token_id": [
14
+ 1,
15
+ 106
16
+ ],
17
+ "image_token_id": 258880,
18
+ "initializer_range": 0.02,
19
+ "model_type": "gemma4",
20
+ "quantization": {
21
+ "group_size": 64,
22
+ "bits": 5,
23
+ "mode": "affine",
24
+ "language_model.model.layers.15.self_attn.k_proj": {
25
+ "bits": 8,
26
+ "group_size": 64,
27
+ "mode": "affine"
28
+ },
29
+ "language_model.model.layers.14.experts.switch_glu.down_proj": {
30
+ "bits": 6,
31
+ "group_size": 64,
32
+ "mode": "affine"
33
+ },
34
+ "language_model.model.layers.6.router.proj": {
35
+ "bits": 8,
36
+ "group_size": 64,
37
+ "mode": "affine"
38
+ },
39
+ "language_model.model.embed_tokens": {
40
+ "bits": 8,
41
+ "group_size": 64,
42
+ "mode": "affine"
43
+ },
44
+ "language_model.model.layers.7.self_attn.q_proj": {
45
+ "bits": 8,
46
+ "group_size": 64,
47
+ "mode": "affine"
48
+ },
49
+ "language_model.model.layers.14.mlp.down_proj": {
50
+ "bits": 6,
51
+ "group_size": 64,
52
+ "mode": "affine"
53
+ },
54
+ "language_model.model.layers.0.self_attn.q_proj": {
55
+ "bits": 8,
56
+ "group_size": 64,
57
+ "mode": "affine"
58
+ },
59
+ "language_model.model.layers.2.mlp.down_proj": {
60
+ "bits": 6,
61
+ "group_size": 64,
62
+ "mode": "affine"
63
+ },
64
+ "language_model.model.layers.0.mlp.down_proj": {
65
+ "bits": 6,
66
+ "group_size": 64,
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+ "mode": "affine"
68
+ },
69
+ "language_model.model.layers.14.self_attn.v_proj": {
70
+ "bits": 8,
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+ "group_size": 64,
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+ "mode": "affine"
73
+ },
74
+ "language_model.model.layers.0.router.proj": {
75
+ "bits": 8,
76
+ "group_size": 64,
77
+ "mode": "affine"
78
+ },
79
+ "language_model.model.layers.0.self_attn.v_proj": {
80
+ "bits": 8,
81
+ "group_size": 64,
82
+ "mode": "affine"
83
+ },
84
+ "language_model.model.layers.28.self_attn.v_proj": {
85
+ "bits": 8,
86
+ "group_size": 64,
87
+ "mode": "affine"
88
+ },
89
+ "language_model.model.layers.25.self_attn.v_proj": {
90
+ "bits": 8,
91
+ "group_size": 64,
92
+ "mode": "affine"
93
+ },
94
+ "language_model.model.layers.8.self_attn.v_proj": {
95
+ "bits": 8,
96
+ "group_size": 64,
97
+ "mode": "affine"
98
+ },
99
+ "language_model.model.layers.24.self_attn.v_proj": {
100
+ "bits": 8,
101
+ "group_size": 64,
102
+ "mode": "affine"
103
+ },
104
+ "language_model.model.layers.13.self_attn.v_proj": {
105
+ "bits": 8,
106
+ "group_size": 64,
107
+ "mode": "affine"
108
+ },
109
+ "language_model.model.layers.0.experts.switch_glu.down_proj": {
110
+ "bits": 6,
111
+ "group_size": 64,
112
+ "mode": "affine"
113
+ },
114
+ "language_model.model.layers.28.self_attn.q_proj": {
115
+ "bits": 8,
116
+ "group_size": 64,
117
+ "mode": "affine"
118
+ },
119
+ "language_model.model.layers.26.self_attn.q_proj": {
120
+ "bits": 8,
121
+ "group_size": 64,
122
+ "mode": "affine"
123
+ },
124
+ "language_model.model.layers.3.self_attn.q_proj": {
125
+ "bits": 8,
126
+ "group_size": 64,
127
+ "mode": "affine"
128
+ },
129
+ "language_model.model.layers.4.self_attn.v_proj": {
130
+ "bits": 8,
131
+ "group_size": 64,
132
+ "mode": "affine"
133
+ },
134
+ "language_model.model.layers.14.self_attn.k_proj": {
135
+ "bits": 8,
136
+ "group_size": 64,
137
+ "mode": "affine"
138
+ },
139
+ "language_model.model.layers.20.experts.switch_glu.down_proj": {
140
+ "bits": 6,
141
+ "group_size": 64,
142
+ "mode": "affine"
143
+ },
144
+ "language_model.model.layers.22.self_attn.k_proj": {
145
+ "bits": 8,
146
+ "group_size": 64,
147
+ "mode": "affine"
148
+ },
149
+ "language_model.model.layers.6.self_attn.v_proj": {
150
+ "bits": 8,
151
+ "group_size": 64,
152
+ "mode": "affine"
153
+ },
154
+ "language_model.model.layers.6.self_attn.q_proj": {
155
+ "bits": 8,
156
+ "group_size": 64,
157
+ "mode": "affine"
158
+ },
159
+ "language_model.model.layers.12.self_attn.v_proj": {
160
+ "bits": 8,
161
+ "group_size": 64,
162
+ "mode": "affine"
163
+ },
164
+ "language_model.model.layers.13.mlp.down_proj": {
165
+ "bits": 6,
166
+ "group_size": 64,
167
+ "mode": "affine"
168
+ },
169
+ "language_model.model.layers.17.self_attn.q_proj": {
170
+ "bits": 8,
171
+ "group_size": 64,
172
+ "mode": "affine"
173
+ },
174
+ "language_model.model.layers.4.experts.switch_glu.down_proj": {
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+ "bits": 6,
176
+ "group_size": 64,
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+ "mode": "affine"
178
+ },
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+ "language_model.model.layers.18.self_attn.q_proj": {
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+ "bits": 8,
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+ "group_size": 64,
182
+ "mode": "affine"
183
+ },
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+ "language_model.model.layers.15.experts.switch_glu.down_proj": {
185
+ "bits": 6,
186
+ "group_size": 64,
187
+ "mode": "affine"
188
+ },
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+ "language_model.model.layers.27.experts.switch_glu.down_proj": {
190
+ "bits": 6,
191
+ "group_size": 64,
192
+ "mode": "affine"
193
+ },
194
+ "language_model.model.layers.20.mlp.down_proj": {
195
+ "bits": 6,
196
+ "group_size": 64,
197
+ "mode": "affine"
198
+ },
199
+ "language_model.model.layers.3.experts.switch_glu.down_proj": {
200
+ "bits": 6,
201
+ "group_size": 64,
202
+ "mode": "affine"
203
+ },
204
+ "language_model.model.layers.16.self_attn.q_proj": {
205
+ "bits": 8,
206
+ "group_size": 64,
207
+ "mode": "affine"
208
+ },
209
+ "language_model.model.layers.18.experts.switch_glu.down_proj": {
210
+ "bits": 6,
211
+ "group_size": 64,
212
+ "mode": "affine"
213
+ },
214
+ "language_model.model.layers.4.self_attn.k_proj": {
215
+ "bits": 8,
216
+ "group_size": 64,
217
+ "mode": "affine"
218
+ },
219
+ "language_model.model.layers.18.self_attn.k_proj": {
220
+ "bits": 8,
221
+ "group_size": 64,
222
+ "mode": "affine"
223
+ },
224
+ "language_model.model.layers.13.experts.switch_glu.down_proj": {
225
+ "bits": 6,
226
+ "group_size": 64,
227
+ "mode": "affine"
228
+ },
229
+ "language_model.model.layers.19.self_attn.k_proj": {
230
+ "bits": 8,
231
+ "group_size": 64,
232
+ "mode": "affine"
233
+ },
234
+ "language_model.model.layers.28.self_attn.k_proj": {
235
+ "bits": 8,
236
+ "group_size": 64,
237
+ "mode": "affine"
238
+ },
239
+ "language_model.model.layers.6.mlp.down_proj": {
240
+ "bits": 6,
241
+ "group_size": 64,
242
+ "mode": "affine"
243
+ },
244
+ "language_model.model.layers.4.mlp.down_proj": {
245
+ "bits": 6,
246
+ "group_size": 64,
247
+ "mode": "affine"
248
+ },
249
+ "language_model.model.layers.11.self_attn.k_proj": {
250
+ "bits": 8,
251
+ "group_size": 64,
252
+ "mode": "affine"
253
+ },
254
+ "language_model.model.layers.24.router.proj": {
255
+ "bits": 8,
256
+ "group_size": 64,
257
+ "mode": "affine"
258
+ },
259
+ "language_model.model.layers.23.mlp.down_proj": {
260
+ "bits": 6,
261
+ "group_size": 64,
262
+ "mode": "affine"
263
+ },
264
+ "language_model.model.layers.24.experts.switch_glu.down_proj": {
265
+ "bits": 6,
266
+ "group_size": 64,
267
+ "mode": "affine"
268
+ },
269
+ "language_model.model.layers.21.self_attn.q_proj": {
270
+ "bits": 8,
271
+ "group_size": 64,
272
+ "mode": "affine"
273
+ },
274
+ "language_model.model.layers.10.experts.switch_glu.down_proj": {
275
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