Instructions to use mlabonne/codellama-2-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mlabonne/codellama-2-7b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "mlabonne/codellama-2-7b") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#5
by SFconvertbot - opened
adapter_model.safetensors
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oid sha256:2e0c15ab5a86cda23891785875348946fbedbca70833eadd369077363bc681ef
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pytorch_model-00001-of-00002.safetensors
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oid sha256:95eafc5941aca9d51f2345b99bcf08db83fa2c460476fe9e883088c2d313945d
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size 9976579144
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pytorch_model-00002-of-00002.safetensors
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oid sha256:2057b64edbda4e5236ff63b840239a7f3153fe1ab26f1a9b1996e11182ae43ff
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size 3500297424
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