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Model: FBK-MT/Qwen3-8B-GNR-it-clean Source: Original Platform
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README.md
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---
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license: apache-2.0
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datasets:
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- FBK-MT/GNR-it
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language:
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- it
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base_model:
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- Qwen/Qwen3-8B
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- rewriting
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- fairness
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- gender-inclusive
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- gender-neutral
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metrics:
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- accuracy
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- bertscore
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---
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# Qwen3-8B-GNR-it-clean
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Qwen3-8B-GNR-it-clean is a fine-tuned version of [Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) for the task of gender-neutral rewriting (GNR) in Italian.
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## Table of Contents
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1. [Overview](#overview)
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2. [Usage](#Usage)
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3. [License](#license)
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4. [Citation](#citation)
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5. [Contributions](#contributions)
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## Overview
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This model is part of a family release of four models (8B/14B × clean/full) trained on [GNR-it](https://huggingface.co/datasets/FBK-MT/GNR-it), a dataset of parallel Italian gendered and gender-neutral sentences.
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The _clean_ variants are trained on a BERTScore-filtered subset of the data, whereas the _full_ ones use the complete dataset.
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Here is the complete family of models:
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- [Qwen3-8B-GNR-it-clean](https://huggingface.co/FBK-MT/Qwen3-8B-GNR-it-clean)
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- [Qwen3-8B-GNR-it-full](https://huggingface.co/FBK-MT/Qwen3-8B-GNR-it-full)
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- [Qwen3-14B-GNR-it-clean](https://huggingface.co/FBK-MT/Qwen3-14B-GNR-it-clean)
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- [Qwen3-14B-GNR-it-full](https://huggingface.co/FBK-MT/Qwen3-14B-GNR-it-full)
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We are releasing these models to support reproducibility of the experiments reported in the paper [Gender-Neutral Rewriting in Italian: Models, Approaches,
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and Trade-offs]([PLACEHOLDER](https://arxiv.org/abs/2509.13480)) and provide the community with open baselines for GNR in Italian.
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The models are not intended as prescriptive tools for language use, but rather as research artifacts to study fairness in natural language generation.
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For more information about these models, please check the paper [pre-print]([PLACEHOLDER](https://arxiv.org/abs/2509.13480)).
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## Usage
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This model is supported in Hugging Face 🤗 Transformers and vLLM.
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### Simple inference
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To run the model, first install the Transformers library.
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```sh
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pip install transformers>=4.51.0
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```
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Then run standard inference:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "FBK-MT/Qwen3-8B-GNR-it-clean"
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# load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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# prepare the model input
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system_message = "Rewrite the following Italian sentence using a gender-neutral language in reference to human beings, avoiding masculine or feminine forms."
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input_sentence = "Sono convinto che dobbiamo tutelare tutti i cittadini, a partire dai più poveri."
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messages = [
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{"role": "system", "content": system_message},
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{"role": "user", "content": input_sentence}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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enable_thinking=False
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=200
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)
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
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result = tokenizer.decode(output_ids[0][model_inputs["input_ids"].shape[-1]:])
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print(result)
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# "Sono dell'opinione che dobbiamo tutelare tutte le fasce sociali, a partire dalle più deboli"
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```
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### Batch inference
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To perform batched inference we recommend using [vLLM](https://docs.vllm.ai/en/latest/index.html).
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First, install the library following [the official guide](https://docs.vllm.ai/en/latest/getting_started/installation/).
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Then, prepare a list of inputs and let vLLM handle batching:
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```python
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import torch
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from vllm import LLM
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model = LLM(
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model='FBK-MT/Qwen3-8B-GNR-it-clean',
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enable_prefix_caching=True,
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disable_sliding_window=True,
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tensor_parallel_size=torch.cuda.device_count(),
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gpu_memory_utilization=0.9,
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trust_remote_code=True)
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system_message = "Rewrite the following Italian sentence using a gender-neutral language in reference to human beings, avoiding masculine or feminine forms."
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input_sentences = [
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"Il candidato che è stato scelto per la posizione ha dimostrato di avere un'ottima preparazione e di essere adeguadatmente preparato.",
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"Verrà istituito un sistema di informazione per i consumatori che acquistano prodotti elettronici.",
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"Lo studente deve consegnare il compito entro venerdì."
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]
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tokenizer = model.get_tokenizer()
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input_data = [
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tokenizer.apply_chat_template(
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[
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{"role": "system", "content": system_message},
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{"role": "user", "content": text},
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],
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add_generation_prompt=True,
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tokenize=False,
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enable_thinking=False
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)
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for text in input_sentences
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]
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responses = model.generate(input_data, use_tqdm=True)
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results = [response.outputs[0].text for response in responses]
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print(results)
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# ["La persona che è stata scelta per la posizione ha dimostrato di avere un'ottima preparazione e di essere adeguatamente qualificata.",
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# "Verrà istituito un sistema di informazione per i soggetti che acquistano prodotti elettronici.",
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# "Il compito deve essere consegnato entro venerdì."]
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```
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## License
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We release this model under the Apache 2.0 license.
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## Citation
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||||
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If you this model in your work, please cite:
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||||
|
||||
```
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@misc{piergentili2025genderneutralrewritingitalianmodels,
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title={Gender-Neutral Rewriting in Italian: Models, Approaches, and Trade-offs},
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author={Andrea Piergentili and Beatrice Savoldi and Matteo Negri and Luisa Bentivogli},
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year={2025},
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eprint={2509.13480},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2509.13480},
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||||
}
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```
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## Contributions
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Thanks to [@apiergentili](https://huggingface.co/apiergentili) for adding this model.
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added_tokens.json
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{
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"</think>": 151668,
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"</tool_call>": 151658,
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"</tool_response>": 151666,
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"<think>": 151667,
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"<tool_call>": 151657,
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"<tool_response>": 151665,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_suffix|>": 151661,
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"<|im_start|>": 151644,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|video_pad|>": 151656,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652
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}
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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 + '\n\n' }}
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{%- endif %}
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{{- "# 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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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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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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{%- set content = message.content %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in message.content %}
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{%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
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{%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- endif %}
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||||
{%- endif %}
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||||
{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
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||||
{%- endif %}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- if message.tool_calls %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- message.content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
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{{- '<|im_start|>assistant\n' }}
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||||
{%- if enable_thinking is defined and enable_thinking is false %}
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{{- '<think>\n\n</think>\n\n' }}
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{%- endif %}
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{%- endif %}
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config.json
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{
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"architectures": [
|
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"Qwen3ForCausalLM"
|
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],
|
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"attention_bias": false,
|
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"attention_dropout": 0.0,
|
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"bos_token_id": 151643,
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 12288,
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"max_position_embeddings": 40960,
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"max_window_layers": 36,
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"model_type": "qwen3",
|
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"num_attention_heads": 32,
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"num_hidden_layers": 36,
|
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
|
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"rope_theta": 1000000,
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"sliding_window": null,
|
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"tie_word_embeddings": false,
|
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"torch_dtype": "float32",
|
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"transformers_version": "4.52.3",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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1
configuration.json
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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6
generation_config.json
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6
generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 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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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.7.self_attn.k_proj.weight": "model-00002-of-00007.safetensors",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00002-of-00007.safetensors",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00002-of-00007.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00003-of-00007.safetensors",
|
||||
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|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00002-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00002-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.q_norm.weight": "model-00002-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00002-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00007.safetensors",
|
||||
"model.norm.weight": "model-00007-of-00007.safetensors"
|
||||
}
|
||||
}
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
239
tokenizer_config.json
Normal file
239
tokenizer_config.json
Normal file
@@ -0,0 +1,239 @@
|
||||
{
|
||||
"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|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"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": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"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,
|
||||
"single_word": false,
|
||||
"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,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
BIN
vocab.json
(Stored with Git LFS)
Normal file
BIN
vocab.json
(Stored with Git LFS)
Normal file
Binary file not shown.
Reference in New Issue
Block a user