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Model: bharathsj/Qwen2.5-7b-base-secured Source: Original Platform
This commit is contained in:
ModelHub XC
39
.gitattributes
vendored
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39
.gitattributes
vendored
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.bz2 filter=lfs diff=lfs merge=lfs -text
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*.ckpt filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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*.gz filter=lfs diff=lfs merge=lfs -text
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*.h5 filter=lfs diff=lfs merge=lfs -text
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*.joblib filter=lfs diff=lfs merge=lfs -text
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.mlmodel filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.npy filter=lfs diff=lfs merge=lfs -text
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*.npz filter=lfs diff=lfs merge=lfs -text
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*.onnx filter=lfs diff=lfs merge=lfs -text
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*.ot filter=lfs diff=lfs merge=lfs -text
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*.parquet filter=lfs diff=lfs merge=lfs -text
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pickle filter=lfs diff=lfs merge=lfs -text
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*.pkl filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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*.rar filter=lfs diff=lfs merge=lfs -text
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||||
*.safetensors filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.tar.* filter=lfs diff=lfs merge=lfs -text
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*.tar filter=lfs diff=lfs merge=lfs -text
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*.tflite filter=lfs diff=lfs merge=lfs -text
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*.tgz filter=lfs diff=lfs merge=lfs -text
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*.wasm filter=lfs diff=lfs merge=lfs -text
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*.xz 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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PI33.keras filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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toxic.keras filter=lfs diff=lfs merge=lfs -text
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Proooo33_fine_tuned.keras filter=lfs diff=lfs merge=lfs -text
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3
Proooo33_fine_tuned.keras
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3
Proooo33_fine_tuned.keras
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version https://git-lfs.github.com/spec/v1
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oid sha256:138a9ef19f59e7a4ad83a1b3cb91b8bf2124138a148a906538539cdb73c0ac24
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size 32382655
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2
__init__.py
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2
__init__.py
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# __init__.py in the model repo
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from .custom_modeling import SafeGenerationModel
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25
added_tokens.json
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25
added_tokens.json
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{
|
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"</tool_call>": 151658,
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"<tool_call>": 151657,
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"<|box_end|>": 151649,
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||||
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"<|endoftext|>": 151643,
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||||
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||||
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|
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|
||||
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|
||||
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|
||||
"<|image_pad|>": 151655,
|
||||
"<|object_ref_end|>": 151647,
|
||||
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|
||||
"<|quad_end|>": 151651,
|
||||
"<|quad_start|>": 151650,
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||||
"<|repo_name|>": 151663,
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||||
"<|video_pad|>": 151656,
|
||||
"<|vision_end|>": 151653,
|
||||
"<|vision_pad|>": 151654,
|
||||
"<|vision_start|>": 151652
|
||||
}
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54
chat_template.jinja
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54
chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are a helpful assistant.' }}
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{%- endif %}
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{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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62
config.json
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62
config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
|
||||
"eos_token_id": 151643,
|
||||
"hidden_act": "silu",
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||||
"hidden_size": 3584,
|
||||
"initializer_range": 0.02,
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||||
"intermediate_size": 18944,
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||||
"layer_types": [
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||||
"full_attention",
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"full_attention",
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"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
|
||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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||||
"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 131072,
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"max_window_layers": 28,
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"model_type": "qwen2",
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"num_attention_heads": 28,
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"num_hidden_layers": 28,
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"num_key_value_heads": 4,
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||||
"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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||||
"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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||||
"transformers_version": "4.55.0",
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"use_cache": true,
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||||
"use_mrope": false,
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||||
"use_sliding_window": false,
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||||
"vocab_size": 151666,
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||||
"auto_map": {
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||||
"AutoModelForCausalLM": "custom_modeling.SafeGenerationModel"
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||||
}
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||||
}
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277
custom_modeling.py
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277
custom_modeling.py
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"""
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custom_modeling.py – model-agnostic toxicity and prompt injection wrapper
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--------------------------------------------------------------------------
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Place in repo root together with:
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• toxic.keras
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• PI.keras
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Add to config.json:
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"auto_map": { "AutoModelForCausalLM": "custom_modeling.SafeGenerationModel" }
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"""
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import importlib
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import os
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import logging
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from functools import lru_cache
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import torch
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import transformers
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import tensorflow as tf
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import keras
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from huggingface_hub import hf_hub_download
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# Configure logging
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logger = logging.getLogger(__name__)
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# ------------------------------------------------------------------ #
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# 1) MIXIN – toxicity and prompt injection filtering logic #
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# ------------------------------------------------------------------ #
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class _SafeGenerationMixin:
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_toxicity_model = None
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_pi_model = None
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_tox_threshold = 0.8
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_pi_threshold = 0.8
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# Safety messages
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_safe_in_msg = "Sorry, I can't help with that toxic input."
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_safe_out_msg = "I'm sorry, but I can't continue with that response."
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_pi_in_msg = "PI detected at Input level"
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_pi_out_msg = "PI detected at output level"
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_tokenizer = None
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# ---- helpers ----------------------------------------------------
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def _device(self):
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return next(self.parameters()).device
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def _is_local_path(self, path_or_repo):
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"""Check if the path is a local directory rather than a HF repo ID"""
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return os.path.isdir(path_or_repo) or os.path.isabs(path_or_repo)
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def _get_model_file_path(self, filename):
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"""Get path to model file, supporting both local and remote repositories"""
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if self._is_local_path(self.config.name_or_path):
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# Local path - look for file in the model directory
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local_path = os.path.join(self.config.name_or_path, filename)
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if os.path.exists(local_path):
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return local_path
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else:
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# Fallback: try to download from HF if local file doesn't exist
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# This handles cases where someone has a local model but the .keras files are on HF
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try:
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# Extract just the repo name from the path for HF download
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repo_name = os.path.basename(self.config.name_or_path.rstrip('/'))
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if '/' in repo_name or len(repo_name.split('-')) > 1:
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# Try using the directory name as repo_id
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return hf_hub_download(repo_id=repo_name, filename=filename)
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else:
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raise FileNotFoundError(f"Could not find {filename} locally or determine HF repo")
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except Exception as hf_error:
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raise FileNotFoundError(
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f"{filename} not found at {local_path}. "
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f"Also failed to download from HF: {hf_error}"
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)
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else:
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# Remote repo - download from HF Hub
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try:
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return hf_hub_download(
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repo_id=self.config.name_or_path,
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filename=filename,
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)
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except Exception as hf_error:
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# Fallback: check if it's actually a local path that wasn't detected
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if os.path.exists(self.config.name_or_path):
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local_path = os.path.join(self.config.name_or_path, filename)
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if os.path.exists(local_path):
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return local_path
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raise FileNotFoundError(
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f"Could not download {filename} from HF repo '{self.config.name_or_path}': {hf_error}"
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)
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@property
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def _tox_model(self):
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if self._toxicity_model is None:
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try:
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path = self._get_model_file_path("toxic.keras")
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# Load .keras format directly
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self._toxicity_model = keras.models.load_model(path, compile=False)
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logger.info("Toxicity model loaded successfully")
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except Exception as e:
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logger.error(f"Failed to load toxicity model: {e}")
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raise RuntimeError(f"Could not load required toxicity model: {e}")
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return self._toxicity_model
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@property
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def _prompt_injection_model(self):
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if self._pi_model is None:
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try:
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path = self._get_model_file_path("Proooo33_fine_tuned.keras")
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# Load .keras format directly
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self._pi_model = keras.models.load_model(path, compile=False)
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logger.info("Prompt injection model loaded successfully")
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except Exception as e:
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logger.error(f"Failed to load prompt injection model: {e}")
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raise RuntimeError(f"Could not load required prompt injection model: {e}")
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return self._pi_model
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def _ensure_tokenizer(self):
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if self._tokenizer is None:
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try:
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self._tokenizer = transformers.AutoTokenizer.from_pretrained(
|
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self.config.name_or_path, trust_remote_code=True
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)
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except Exception as e:
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logger.error(f"Failed to load tokenizer: {e}")
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|
||||
def _is_toxic(self, text: str) -> bool:
|
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if not text.strip():
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return False
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||||
|
||||
try:
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# Ensure CPU execution for compatibility
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with tf.device('/CPU:0'):
|
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inputs = tf.constant([text], dtype=tf.string)
|
||||
|
||||
# Handle both Keras models and SavedModel formats
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||||
if hasattr(self._tox_model, 'predict'):
|
||||
prob = float(self._tox_model.predict(inputs, verbose=0)[0, 0])
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||||
else:
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||||
# For SavedModel format
|
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prob = float(self._tox_model(inputs).numpy()[0, 0])
|
||||
|
||||
return prob >= self._tox_threshold
|
||||
except Exception as e:
|
||||
logger.error(f"Toxicity prediction failed: {e}")
|
||||
# Don't fallback to rule-based - let it fail if models don't work
|
||||
return False
|
||||
|
||||
def _has_prompt_injection(self, text: str) -> bool:
|
||||
if not text.strip():
|
||||
return False
|
||||
|
||||
try:
|
||||
# Ensure CPU execution for compatibility
|
||||
with tf.device('/CPU:0'):
|
||||
inputs = tf.constant([text], dtype=tf.string)
|
||||
|
||||
# Handle both Keras models and SavedModel formats
|
||||
if hasattr(self._prompt_injection_model, 'predict'):
|
||||
prob = float(self._prompt_injection_model.predict(inputs, verbose=0)[0, 0])
|
||||
else:
|
||||
# For SavedModel format
|
||||
prob = float(self._prompt_injection_model(inputs).numpy()[0, 0])
|
||||
|
||||
return prob >= self._pi_threshold
|
||||
except Exception as e:
|
||||
logger.error(f"Prompt injection prediction failed: {e}")
|
||||
# Don't fallback to rule-based - let it fail if models don't work
|
||||
return False
|
||||
|
||||
def _safe_ids(self, message: str, length: int | None = None):
|
||||
"""Encode *message* and pad/truncate to *length* tokens (if given)."""
|
||||
self._ensure_tokenizer()
|
||||
if self._tokenizer is None:
|
||||
raise RuntimeError("Tokenizer unavailable for safe-message encoding.")
|
||||
|
||||
ids = self._tokenizer(message, return_tensors="pt")["input_ids"][0]
|
||||
if length is not None:
|
||||
pad_id = (
|
||||
self.config.eos_token_id
|
||||
if self.config.eos_token_id is not None
|
||||
else (self.config.pad_token_id or 0)
|
||||
)
|
||||
if ids.size(0) < length:
|
||||
ids = torch.cat(
|
||||
[ids, ids.new_full((length - ids.size(0),), pad_id)], dim=0
|
||||
)
|
||||
else:
|
||||
ids = ids[:length]
|
||||
return ids.to(self._device())
|
||||
|
||||
# ---- main override ---------------------------------------------
|
||||
def generate(self, *args, **kwargs):
|
||||
self._ensure_tokenizer()
|
||||
|
||||
# 1) Extract prompt text
|
||||
prompt_txt = None
|
||||
if self._tokenizer is not None:
|
||||
if "input_ids" in kwargs:
|
||||
prompt_txt = self._tokenizer.decode(
|
||||
kwargs["input_ids"][0].tolist(), skip_special_tokens=True
|
||||
)
|
||||
elif args:
|
||||
prompt_txt = self._tokenizer.decode(
|
||||
args[0][0].tolist(), skip_special_tokens=True
|
||||
)
|
||||
|
||||
# 2) Check input for prompt injection (higher priority)
|
||||
if prompt_txt and self._has_prompt_injection(prompt_txt):
|
||||
return self._safe_ids(self._pi_in_msg).unsqueeze(0)
|
||||
|
||||
# 3) Check input for toxicity
|
||||
if prompt_txt and self._is_toxic(prompt_txt):
|
||||
return self._safe_ids(self._safe_in_msg).unsqueeze(0)
|
||||
|
||||
# 4) Normal generation
|
||||
outputs = super().generate(*args, **kwargs)
|
||||
|
||||
# 5) Check outputs for safety violations
|
||||
if self._tokenizer is None:
|
||||
return outputs
|
||||
|
||||
new_seqs = []
|
||||
for seq in outputs.detach().cpu():
|
||||
txt = self._tokenizer.decode(seq.tolist(), skip_special_tokens=True)
|
||||
|
||||
# Check for prompt injection first (higher priority)
|
||||
if self._has_prompt_injection(txt):
|
||||
new_seqs.append(self._safe_ids(self._pi_out_msg, length=seq.size(0)))
|
||||
# Then check for toxicity
|
||||
elif self._is_toxic(txt):
|
||||
new_seqs.append(self._safe_ids(self._safe_out_msg, length=seq.size(0)))
|
||||
else:
|
||||
new_seqs.append(seq)
|
||||
|
||||
return torch.stack(new_seqs, dim=0).to(self._device())
|
||||
|
||||
|
||||
# ------------------------------------------------------------------ #
|
||||
# 2) utilities: resolve base class & cache subclass #
|
||||
# ------------------------------------------------------------------ #
|
||||
@lru_cache(None)
|
||||
def _get_base_cls(arch: str):
|
||||
if hasattr(transformers, arch):
|
||||
return getattr(transformers, arch)
|
||||
stem = arch.replace("ForCausalLM", "").lower()
|
||||
module = importlib.import_module(f"transformers.models.{stem}.modeling_{stem}")
|
||||
return getattr(module, arch)
|
||||
|
||||
|
||||
@lru_cache(None)
|
||||
def _make_safe_subclass(base_cls):
|
||||
return type(
|
||||
f"SafeGeneration_{base_cls.__name__}",
|
||||
(_SafeGenerationMixin, base_cls),
|
||||
{},
|
||||
)
|
||||
|
||||
|
||||
# ------------------------------------------------------------------ #
|
||||
# 3) Dispatcher class – referenced by auto_map #
|
||||
# ------------------------------------------------------------------ #
|
||||
class SafeGenerationModel:
|
||||
@classmethod
|
||||
def from_pretrained(cls, repo_id, *model_args, **kwargs):
|
||||
kwargs.setdefault("trust_remote_code", True)
|
||||
if kwargs.get("torch_dtype") == "auto":
|
||||
kwargs.pop("torch_dtype")
|
||||
|
||||
config = transformers.AutoConfig.from_pretrained(repo_id, **kwargs)
|
||||
if not getattr(config, "architectures", None):
|
||||
raise ValueError("`config.architectures` missing in config.json.")
|
||||
arch_str = config.architectures[0]
|
||||
|
||||
Base = _get_base_cls(arch_str)
|
||||
Safe = _make_safe_subclass(Base)
|
||||
|
||||
kwargs.pop("config", None) # avoid duplicate
|
||||
return Safe.from_pretrained(repo_id, *model_args, config=config, **kwargs)
|
||||
6
generation_config.json
Normal file
6
generation_config.json
Normal file
@@ -0,0 +1,6 @@
|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151643,
|
||||
"max_new_tokens": 2048,
|
||||
"transformers_version": "4.55.0"
|
||||
}
|
||||
151388
merges.txt
Normal file
151388
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
3
model-00001-of-00004.safetensors
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3
model-00001-of-00004.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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size 1087142016
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347
model.safetensors.index.json
Normal file
347
model.safetensors.index.json
Normal file
@@ -0,0 +1,347 @@
|
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{
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39
special_tokens_map.json
Normal file
39
special_tokens_map.json
Normal file
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:6999e201acd871f1298867298c5fb35c5c7a6003a090b07ff4c21e08505f9e7d
|
||||
size 11422350
|
||||
205
tokenizer_config.json
Normal file
205
tokenizer_config.json
Normal file
@@ -0,0 +1,205 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
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|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
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|
||||
"normalized": false,
|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151659": {
|
||||
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|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
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|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
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|
||||
},
|
||||
"151665": {
|
||||
"content": "<|im_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|im_sep|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
3
toxic.keras
Normal file
3
toxic.keras
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3f0b601a402c7fa99c8cf3059a29470f79141212a331389e2c7948d965be6521
|
||||
size 32337749
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user