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Model: vilm/Quyen-Mini-v0.1 Source: Original Platform
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README.md
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---
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language:
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- en
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license: other
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library_name: transformers
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datasets:
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- teknium/OpenHermes-2.5
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- LDJnr/Capybara
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- Intel/orca_dpo_pairs
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- argilla/distilabel-capybara-dpo-7k-binarized
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pipeline_tag: text-generation
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model-index:
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- name: Quyen-Mini-v0.1
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 39.33
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 60.57
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 43.93
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 46.44
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 59.12
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 27.45
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vilm/Quyen-Mini-v0.1
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name: Open LLM Leaderboard
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---
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# Quyen
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<img src="quyen.webp" width="512" height="512" alt="Quyen">
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# Model Description
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Quyen is our first flagship LLM series based on the Qwen1.5 family. We introduced 6 different versions:
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- **Quyen-SE (0.5B)**
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- **Quyen-Mini (1.8B)**
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- **Quyen (4B)**
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- **Quyen-Plus (7B)**
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- **Quyen-Pro (14B)**
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- **Quyen-Pro-Max (72B)**
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All models were trained with SFT and DPO using the following dataset:
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- *OpenHermes-2.5* by **Teknium**
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- *Capyabara* by **LDJ**
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- *argilla/distilabel-capybara-dpo-7k-binarized* by **argilla**
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- *orca_dpo_pairs* by **Intel**
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- and Private Data by **Ontocord** & **BEE-spoke-data**
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# Prompt Template
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- All Quyen models use ChatML as the default template:
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```
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<|im_start|>system
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You are a sentient, superintelligent artificial general intelligence, here to teach and assist me.<|im_end|>
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<|im_start|>user
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Hello world.<|im_end|>
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<|im_start|>assistant
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```
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- You can also use `apply_chat_template`:
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```python
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messages = [
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{"role": "system", "content": "You are a sentient, superintelligent artificial general intelligence, here to teach and assist me."},
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{"role": "user", "content": "Hello world."}
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]
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gen_input = tokenizer.apply_chat_template(message, return_tensors="pt")
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model.generate(**gen_input)
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```
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# Benchmarks:
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- Coming Soon! We will update the benchmarks later
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# Acknowledgement
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- We're incredibly grateful to **Tensoic** and **Ontocord** for their generous support with compute and data preparation.
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- Special thanks to the Qwen team for letting us access the models early for these amazing finetunes.
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_vilm__Quyen-Mini-v0.1)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |46.14|
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|AI2 Reasoning Challenge (25-Shot)|39.33|
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|HellaSwag (10-Shot) |60.57|
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|MMLU (5-Shot) |43.93|
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|TruthfulQA (0-shot) |46.44|
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|Winogrande (5-shot) |59.12|
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|GSM8k (5-shot) |27.45|
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added_tokens.json
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{
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"<|endoftext|>": 151643,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644
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}
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config.json
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{
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"_name_or_path": "vilm/Quyen-Mini-4e",
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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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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 5504,
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"max_position_embeddings": 8192,
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"max_window_layers": 21,
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"model_type": "qwen2",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"num_key_value_heads": 16,
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"rms_norm_eps": 1e-06,
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"rope_theta": 1000000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.0.dev0",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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generation_config.json
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{
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"do_sample": true,
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"max_length": 4096,
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"temperature": 0.7,
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"top_p": 0.8,
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"transformers_version": "4.38.0.dev0"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7ee8ef00dbdb3abc556cc68dfc3439bef519cc8c497f61a9fb1fde2fae3647f1
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size 3673754713
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BIN
quyen.webp
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quyen.webp
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"<|im_start|>",
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"<|im_end|>"
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"content": "<|im_end|>",
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"rstrip": false,
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{
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"add_prefix_space": false,
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"additional_special_tokens": [
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"<|im_start|>",
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"<|im_end|>"
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],
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"bos_token": "<|im_end|>",
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"chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
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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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"unk_token": null
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}
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vocab.json
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