Instructions to use mohammedfazilvamos/trained-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mohammedfazilvamos/trained-model 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, "mohammedfazilvamos/trained-model") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from mohammedfazilvamos/trained-model: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/mohammedfazilvamos/trained-model/resolve/main/adapter_model.bin
- Command line
-
hf download hf://mohammedfazilvamos/trained-model/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/mohammedfazilvamos/trained-model/resolve/main/adapter_model.bin
134 MB
- Xet hash:
- f48e125b5cb47efa48215af30b88110286d681130279ceb9445020e8de4c5415
- Size of remote file:
- 134 MB
- SHA256:
- 4af5afd573e6d658e01613652692ebbf38d320b4de25633a3c2a477c65ace86a
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