Instructions to use akashmaggon/llam2fullmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use akashmaggon/llam2fullmodel with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "akashmaggon/llam2fullmodel") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from akashmaggon/llam2fullmodel: direct link, hf CLI and curl.
- Browser
- Download file 80.1 MB
-
https://huggingface.co/akashmaggon/llam2fullmodel/resolve/main/adapter_model.bin
- Command line
-
hf download hf://akashmaggon/llam2fullmodel/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/akashmaggon/llam2fullmodel/resolve/main/adapter_model.bin
80.1 MB
- Xet hash:
- b8606da865cb2eaa4194fcdf5b7d1538f3d072dae6e2b3bff58ac179940bf485
- Size of remote file:
- 80.1 MB
- SHA256:
- a93849fad7be4c650c68ae91ad85f92913edc3176f23ce9a294b834023fb8761
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