Instructions to use bane5631/e525d81c-2731-44fa-9a33-4b1a312ea95e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bane5631/e525d81c-2731-44fa-9a33-4b1a312ea95e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.3") model = PeftModel.from_pretrained(base_model, "bane5631/e525d81c-2731-44fa-9a33-4b1a312ea95e") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from bane5631/e525d81c-2731-44fa-9a33-4b1a312ea95e: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/bane5631/e525d81c-2731-44fa-9a33-4b1a312ea95e/resolve/main/adapter_model.bin
- Command line
-
hf download hf://bane5631/e525d81c-2731-44fa-9a33-4b1a312ea95e/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/bane5631/e525d81c-2731-44fa-9a33-4b1a312ea95e/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- 1a311c1c6770cf5602858782e752b0e6bf241a8bc2595f193fc4e2233e7110ef
- Size of remote file:
- 84 MB
- SHA256:
- 3f5f66f8a3b88cf1ac39b72d836fb280aa38918f2458fc3add1013062ecde5e4
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