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cs2764
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GLM-4.7-PRISM-mlx-6Bit

Text Generation
Transformers
Safetensors
MLX
English
Chinese
glm4_moe
abliteration
SOTA Abliteration Pipeline - PRISM
glm
quantized
finetuned
uncensored
abliterated
mlx-my-repo
conversational
6-bit
Model card Files
xet
 Community
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  1. .cache/._huggingface +0 -0
  2. .gitattributes +1 -0
  3. README.md +54 -0
  4. chat_template.jinja +86 -0
  5. config.json +53 -0
  6. generation_config.json +10 -0
  7. model-00001-of-00054.safetensors +3 -0
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.cache/._huggingface ADDED
Binary file (4.1 kB). View file
 
.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 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: mit
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+ base_model: Ex0bit/GLM-4.7-PRISM
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+ model_name: Elbaz-GLM-4.7-PRISM
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+ tags:
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+ - abliteration
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+ - SOTA Abliteration Pipeline - PRISM
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+ - glm
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+ - glm4_moe
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+ - quantized
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+ - finetuned
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+ - uncensored
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+ - abliterated
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+ - mlx
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+ - mlx-my-repo
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+ language:
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+ - en
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+ - zh
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # cs2764/GLM-4.7-PRISM-mlx-6Bit
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+
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+ The Model [cs2764/GLM-4.7-PRISM-mlx-6Bit](https://huggingface.co/cs2764/GLM-4.7-PRISM-mlx-6Bit) was converted to MLX format from [Ex0bit/GLM-4.7-PRISM](https://huggingface.co/Ex0bit/GLM-4.7-PRISM) using mlx-lm version **0.30.4**.
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+
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+ ## Quantization Details
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+
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+ This model was converted with the following quantization settings:
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+
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+ - **Quantization Strategy**: 6-bit quantization
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+ - **Average bits per weight**: 6.502
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+
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+ ## Use with mlx
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+
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+ ```bash
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+ pip install mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("cs2764/GLM-4.7-PRISM-mlx-6Bit")
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+
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+ prompt="hello"
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+
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+ if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
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+ messages = [{"role": "user", "content": prompt}]
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+ prompt = tokenizer.apply_chat_template(
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+ messages, tokenize=False, add_generation_prompt=True
51
+ )
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+
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+ response = generate(model, tokenizer, prompt=prompt, verbose=True)
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+ ```
chat_template.jinja ADDED
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+ [gMASK]<sop>
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+ {%- if tools -%}
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+ <|system|>
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+ # Tools
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+
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+ You may call one or more functions to assist with the user query.
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+
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+ You are provided with function signatures within <tools></tools> XML tags:
9
+ <tools>
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+ {% for tool in tools %}
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+ {{ tool | tojson(ensure_ascii=False) }}
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+ {% endfor %}
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+ </tools>
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+
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+ For each function call, output the function name and arguments within the following XML format:
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+ <tool_call>{function-name}<arg_key>{arg-key-1}</arg_key><arg_value>{arg-value-1}</arg_value><arg_key>{arg-key-2}</arg_key><arg_value>{arg-value-2}</arg_value>...</tool_call>{%- endif -%}
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+ {%- macro visible_text(content) -%}
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+ {%- if content is string -%}
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+ {{- content }}
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+ {%- elif content is iterable and content is not mapping -%}
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+ {%- for item in content -%}
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+ {%- if item is mapping and item.type == 'text' -%}
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+ {{- item.text }}
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+ {%- elif item is string -%}
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+ {{- item }}
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+ {%- endif -%}
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+ {%- endfor -%}
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+ {%- else -%}
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+ {{- content }}
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+ {%- endif -%}
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+ {%- endmacro -%}
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+ {%- set ns = namespace(last_user_index=-1) %}
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+ {%- for m in messages %}
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+ {%- if m.role == 'user' %}
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+ {% set ns.last_user_index = loop.index0 -%}
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+ {%- endif %}
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+ {%- endfor %}
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+ {% for m in messages %}
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+ {%- if m.role == 'user' -%}<|user|>{{ visible_text(m.content) }}
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+ {%- elif m.role == 'assistant' -%}
41
+ <|assistant|>
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+ {%- set reasoning_content = '' %}
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+ {%- set content = visible_text(m.content) %}
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+ {%- if m.reasoning_content is string %}
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+ {%- set reasoning_content = m.reasoning_content %}
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+ {%- else %}
47
+ {%- if '</think>' in content %}
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+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
50
+ {%- endif %}
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+ {%- endif %}
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+ {%- if ((clear_thinking is defined and not clear_thinking) or loop.index0 > ns.last_user_index) and reasoning_content -%}
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+ {{ '<think>' + reasoning_content.strip() + '</think>'}}
54
+ {%- else -%}
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+ {{ '</think>' }}
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+ {%- endif -%}
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+ {%- if content.strip() -%}
58
+ {{ content.strip() }}
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+ {%- endif -%}
60
+ {% if m.tool_calls %}
61
+ {% for tc in m.tool_calls %}
62
+ {%- if tc.function %}
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+ {%- set tc = tc.function %}
64
+ {%- endif %}
65
+ {{- '<tool_call>' + tc.name -}}
66
+ {% set _args = tc.arguments %}{% for k, v in _args.items() %}<arg_key>{{ k }}</arg_key><arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>{% endfor %}</tool_call>{% endfor %}
67
+ {% endif %}
68
+ {%- elif m.role == 'tool' -%}
69
+ {%- if m.content is string -%}
70
+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
71
+ {{- '<|observation|>' }}
72
+ {%- endif %}
73
+ {{- '<tool_response>' }}
74
+ {{- m.content }}
75
+ {{- '</tool_response>' }}
76
+ {%- else -%}
77
+ <|observation|>{% for tr in m.content %}
78
+ <tool_response>{{ tr.output if tr.output is defined else tr }}</tool_response>{% endfor -%}
79
+ {% endif -%}
80
+ {%- elif m.role == 'system' -%}
81
+ <|system|>{{ visible_text(m.content) }}
82
+ {%- endif -%}
83
+ {%- endfor -%}
84
+ {%- if add_generation_prompt -%}
85
+ <|assistant|>{{- '</think>' if (enable_thinking is defined and not enable_thinking) else '<think>' -}}
86
+ {%- endif -%}
config.json ADDED
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+ {
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+ "architectures": [
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+ "Glm4MoeForCausalLM"
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+ ],
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+ "attention_bias": true,
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+ "attention_dropout": 0.0,
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+ "dtype": "bfloat16",
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+ "eos_token_id": [
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+ 151329,
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+ "first_k_dense_replace": 3,
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+ "head_dim": 128,
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+ "hidden_act": "silu",
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+ "hidden_size": 5120,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 12288,
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+ "max_position_embeddings": 202752,
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+ "model_type": "glm4_moe",
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+ "moe_intermediate_size": 1536,
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+ "n_group": 1,
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+ "n_routed_experts": 160,
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+ "n_shared_experts": 1,
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+ "norm_topk_prob": true,
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+ "num_attention_heads": 96,
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+ "num_experts_per_tok": 8,
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+ "num_hidden_layers": 92,
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+ "num_key_value_heads": 8,
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+ "num_nextn_predict_layers": 0,
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+ "pad_token_id": 151329,
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+ "partial_rotary_factor": 0.5,
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+ "quantization": {
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+ "group_size": 64,
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+ "bits": 6,
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+ "mode": "affine"
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+ },
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+ "quantization_config": {
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+ "group_size": 64,
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+ "bits": 6,
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+ "mode": "affine"
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+ },
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 1000000,
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+ "routed_scaling_factor": 2.5,
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+ "tie_word_embeddings": false,
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+ "topk_group": 1,
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+ "transformers_version": "4.57.3",
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+ "use_cache": true,
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+ "use_qk_norm": true,
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+ "vocab_size": 151552
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+ }
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