End of training
Browse files
README.md
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---
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base_model: meta-llama/CodeLlama-7b-Instruct-hf
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library_name:
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model_name:
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tags:
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- generated_from_trainer
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- trl
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licence: license
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---
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# Model Card for
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This model is a fine-tuned version of [meta-llama/CodeLlama-7b-Instruct-hf](https://huggingface.co/meta-llama/CodeLlama-7b-Instruct-hf).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="basharatwali/
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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### Framework versions
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- PEFT 0.14.1.dev0
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- TRL: 0.13.0
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- Transformers: 4.48.0.dev0
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- Pytorch: 2.5.1+cu121
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---
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base_model: meta-llama/CodeLlama-7b-Instruct-hf
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library_name: transformers
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model_name: CodeLlama-Instruct-Python-7b
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tags:
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- generated_from_trainer
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- trl
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licence: license
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---
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# Model Card for CodeLlama-Instruct-Python-7b
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This model is a fine-tuned version of [meta-llama/CodeLlama-7b-Instruct-hf](https://huggingface.co/meta-llama/CodeLlama-7b-Instruct-hf).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="basharatwali/CodeLlama-Instruct-Python-7b", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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### Framework versions
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- TRL: 0.13.0
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- Transformers: 4.48.0.dev0
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- Pytorch: 2.5.1+cu121
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adapter_model.safetensors
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runs/Jan06_06-55-43_2db6e875cc75/events.out.tfevents.1736146549.2db6e875cc75.518.0
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tokenizer.json
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"strategy": "LongestFirst",
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