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--- |
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license: apache-2.0 |
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--- |
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base_model: |
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- Qwen/Qwen2.5-0.5B-Instruct |
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--- |
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This model is aimed at Chain of Thought and has been trained on human generated, AI Reasoned questions and answers https://huggingface.co/datasets/KingNish/reasoning-base-20k . |
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# Uploaded model |
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- **Developed by:** ewre324 |
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- **License:** apache-2.0 |
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- **Finetuned from model :** Qwen/Qwen2.5-0.5B-Instruct |
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## Requirements |
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The code of Qwen2.5 has been in the latest Hugging face `transformers` and we advise you to use the latest version of `transformers`. |
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With `transformers<4.37.0`, you will encounter the following error: |
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``` |
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KeyError: 'qwen2' |
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## Quickstart |
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Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents. |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "Qwen/Qwen2.5-0.5B-Instruct" |
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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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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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prompt = "Give me a short introduction to large language model." |
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messages = [ |
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{"role": "system", "content": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant."}, |
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{"role": "user", "content": prompt} |
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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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) |
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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=512 |
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) |
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generated_ids = [ |
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) |
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] |
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
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``` |
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## Evaluation & Performance |
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TODO |
