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- model-00002-of-00002.safetensors +1 -1
- tokenizer_config.json +2 -2
README.md
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license: other
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license_name: katanemo-research
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license_link: >-
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https://huggingface.co/katanemolabs/Arch-Function-
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base_model:
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- Qwen/Qwen2.5-
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language:
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- en
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pipeline_tag: text-generation
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library_name: transformers
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---
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# katanemo/Arch-Function-
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## Overview
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The Katanemo Arch-Function collection of large language models (LLMs) is a collection state-of-the-art (SOTA) LLMs specifically designed for **function calling** tasks. The models are designed to understand complex function signatures, identify required parameters, and produce accurate function call outputs based on natural language prompts. Achieving performance on par with GPT-4, these models set a new benchmark in the domain of function-oriented tasks, making them suitable for scenarios where automated API interaction and function execution is crucial.
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<td>63.41%</td>
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<td>82.93%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle;">
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<td>6</td>
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<td>o1-preview-2024-09-12 (Prompt)</td>
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<td>73.17%</td>
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<td>74.60%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; font-weight: bold;">
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<td> </td>
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<td>Arch-Function-7B</td>
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<td>58.44%</td>
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<td>85.58%</td>
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<td>88.14%</td>
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<td>69.08%</td>
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<td>20.50%</td>
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<td>92.68%</td>
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<td>74.05%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; ">
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<td>9</td>
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<td>Gemini-1.5-Flash-002 (Prompt)</td>
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<td>85.37%</td>
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<td>78.54%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; ">
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<td>12</td>
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<td>Claude-3.5-Sonnet-20240620 (FC)</td>
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<td>75.61%</td>
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<td>49.44%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; font-weight: bold;">
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<td> </td>
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<td>Arch-Function-3B</td>
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<td>56.57%</td>
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<td>83.62%</td>
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<td>85.36%</td>
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<td>66.90%</td>
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<td>19.50%</td>
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<td>97.56%</td>
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<td>70.99%</td>
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</tr>
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</tr>
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<tr style="text-align: center; vertical-align: middle; font-weight: bold;">
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<td> </td>
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<td>Arch-Function-1.5B</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; ">
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<td>21</td>
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<td>Llama-3.1-70B-Instruct (Prompt)</td>
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# Requirements
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The code of Arch-Function-
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```bash
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pip install transformers>=4.37.0
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```
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from typing import Any, Dict, List
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "katanemo/Arch-Function-
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model = AutoModelForCausalLM.from_pretrained(
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model_name, device_map="auto", torch_dtype="auto", trust_remote_code=True
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)
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# License
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Katanemo Arch-Function collection is distributed under the [Katanemo license](https://huggingface.co/katanemolabs/Arch-Function-
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license: other
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license_name: katanemo-research
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license_link: >-
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https://huggingface.co/katanemolabs/Arch-Function-3B/blob/main/LICENSE
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base_model:
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- Qwen/Qwen2.5-Coder-3B-Instruct
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language:
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- en
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pipeline_tag: text-generation
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library_name: transformers
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---
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# katanemo/Arch-Function-3B
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## Overview
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The Katanemo Arch-Function collection of large language models (LLMs) is a collection state-of-the-art (SOTA) LLMs specifically designed for **function calling** tasks. The models are designed to understand complex function signatures, identify required parameters, and produce accurate function call outputs based on natural language prompts. Achieving performance on par with GPT-4, these models set a new benchmark in the domain of function-oriented tasks, making them suitable for scenarios where automated API interaction and function execution is crucial.
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<td>63.41%</td>
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<td>82.93%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; font-weight: bold;">
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<td> </td>
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<td>Arch-Function-7B</td>
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<td>59.62%</td>
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<td>86.83%</td>
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<td>88.07%</td>
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<td>71.57%</td>
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<td>21.00%</td>
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<td>95.12%</td>
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<td>73.63%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle;">
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<td>6</td>
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<td>o1-preview-2024-09-12 (Prompt)</td>
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<td>73.17%</td>
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<td>74.60%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; ">
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<td>9</td>
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<td>Gemini-1.5-Flash-002 (Prompt)</td>
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<td>85.37%</td>
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<td>78.54%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; font-weight: bold;">
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<td> </td>
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<td>Arch-Function-3B</td>
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<td>57.69%</td>
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<td>85.19%</td>
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<td>86.18%</td>
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<td>71.21%</td>
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<td>17.50%</td>
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<td>90.24%</td>
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<td>72.88%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; ">
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<td>12</td>
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<td>Claude-3.5-Sonnet-20240620 (FC)</td>
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<td>75.61%</td>
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<td>49.44%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; font-weight: bold;">
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<td> </td>
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<td>Arch-Function-1.5B</td>
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<td>56.20%</td>
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<td>84.40%</td>
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<td>83.96%</td>
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<td>69.36%</td>
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<td>15.88%</td>
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<td>87.80%</td>
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<td>74.39%</td>
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</tr>
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<tr style="text-align: center; vertical-align: middle; ">
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<td>21</td>
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<td>Llama-3.1-70B-Instruct (Prompt)</td>
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# Requirements
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The code of Arch-Function-3B has been in the Hugging Face `transformers` library and we advise you to install latest version:
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```bash
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pip install transformers>=4.37.0
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```
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from typing import Any, Dict, List
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "katanemo/Arch-Function-3B"
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model = AutoModelForCausalLM.from_pretrained(
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model_name, device_map="auto", torch_dtype="auto", trust_remote_code=True
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)
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# License
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Katanemo Arch-Function collection is distributed under the [Katanemo license](https://huggingface.co/katanemolabs/Arch-Function-3B/blob/main/LICENSE).
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config.json
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{
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"_name_or_path": "Qwen/Qwen2.5-3B-Instruct",
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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"max_position_embeddings": 32768,
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"max_window_layers":
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"model_type": "qwen2",
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"num_attention_heads": 16,
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"num_hidden_layers": 36,
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{
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"_name_or_path": "Qwen/Qwen2.5-Coder-3B-Instruct",
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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"max_position_embeddings": 32768,
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"max_window_layers": 36,
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"model_type": "qwen2",
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"num_attention_heads": 16,
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"num_hidden_layers": 36,
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model-00001-of-00002.safetensors
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tokenizer_config.json
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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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"model_max_length":
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"pad_token": "<|endoftext|>",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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}
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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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"model_max_length": 32768,
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"pad_token": "<|endoftext|>",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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}
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