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--- |
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language: |
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- en |
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- th |
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library_name: transformers |
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base_model: |
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- meta-llama/Llama-3.2-1B |
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tags: |
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- text-generation |
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pipeline_tag: text-generation |
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inference: |
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parameters: |
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temperature: 0.5 |
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widget: |
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- messages: |
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- role: user |
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content: What is your favorite condiment? |
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--- |
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extra_gated_description: If you want to learn more about how we process your personal data, please read our <a href="https://mistral.ai/terms/">Privacy Policy</a>. |
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--- |
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--- |
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# LLaMA 3 Fine-Tuned Model |
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This is a fine-tuned version of the LLaMA 3 model . Below is an example of how to use it: |
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## Example Usage |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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# Load model and tokenizer |
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tokenizer = AutoTokenizer.from_pretrained("Pection/llama3-finetune") |
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model = AutoModelForCausalLM.from_pretrained("Pection/llama3-finetune") |
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# Generate response |
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prompt = "Where is Bangkok?" |
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inputs = tokenizer(prompt, return_tensors="pt") |
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outputs = model.generate(**inputs, max_new_tokens=50) |
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response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print(response) |
