Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +53 -0
- adapter_config.json +46 -0
- adapter_model.safetensors +3 -0
- chat_template.jinja +54 -0
- tokenizer.json +3 -0
- tokenizer_config.json +29 -0
.gitattributes
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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base_model: Qwen/Qwen2.5-3B-Instruct
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library_name: peft
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license: mit
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tags:
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- lora
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- json
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- structured-output
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- text-generation
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- qwen2
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- sft
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- trl
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language:
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- en
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pipeline_tag: text-generation
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---
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# Qwen2.5-3B JSON Structured Output (LoRA)
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A LoRA adapter that enhances Qwen2.5-3B-Instruct for extracting structured JSON from unstructured text.
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## Training Details
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| Parameter | Value |
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|-----------|-------|
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| Base Model | Qwen/Qwen2.5-3B-Instruct |
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| Method | QLoRA (4-bit NF4) |
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| LoRA Rank | 16 |
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| LoRA Alpha | 32 |
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| Target Modules | q,k,v,o,gate,up,down |
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| Trainable Params | 29.9M (1.76%) |
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| Training Examples | 20 curated |
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| Epochs | 5 |
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| Learning Rate | 5e-5 |
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| Final Loss | 1.506 |
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| Hardware | NVIDIA RTX 3090 x2 |
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## Quick Start
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
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from peft import PeftModel
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import torch, json
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bnb = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=torch.bfloat16)
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tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-3B-Instruct")
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model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-3B-Instruct", quantization_config=bnb, device_map="auto")
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model = PeftModel.from_pretrained(model, "2reb/Qwen2.5-3B-JSON-StructuredOutput")
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```
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## License
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MIT
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adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": null,
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"base_model_name_or_path": "Qwen/Qwen2.5-3B-Instruct",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"peft_version": "0.18.1",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"down_proj",
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"v_proj",
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"o_proj",
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"q_proj",
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"up_proj",
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"gate_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2efd75e3133793f380c9035fff509df56e1406e2055f2724de84fdca71c8096f
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size 59934640
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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 Qwen, created by Alibaba Cloud. 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 Qwen, created by Alibaba Cloud. You 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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| 53 |
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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size 11421892
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"backend": "tokenizers",
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| 4 |
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"bos_token": null,
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|im_end|>",
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"errors": "replace",
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| 8 |
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"extra_special_tokens": [
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"<|im_start|>",
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"<|im_end|>",
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"<|object_ref_start|>",
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| 12 |
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"<|object_ref_end|>",
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| 13 |
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"<|box_start|>",
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| 14 |
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"<|box_end|>",
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| 15 |
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"<|quad_start|>",
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"<|quad_end|>",
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"<|vision_start|>",
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"<|vision_end|>",
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"<|vision_pad|>",
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"<|image_pad|>",
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"<|video_pad|>"
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],
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"is_local": false,
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| 24 |
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"model_max_length": 131072,
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| 25 |
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"pad_token": "<|endoftext|>",
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| 26 |
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"split_special_tokens": false,
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| 27 |
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"tokenizer_class": "Qwen2Tokenizer",
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| 28 |
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"unk_token": null
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| 29 |
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}
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