Instructions to use SamChen888/Mistral-RDE-Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SamChen888/Mistral-RDE-Finetuned with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.3-bnb-4bit") model = PeftModel.from_pretrained(base_model, "SamChen888/Mistral-RDE-Finetuned") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download checkpoint-348/optimizer.pt from SamChen888/Mistral-RDE-Finetuned: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/SamChen888/Mistral-RDE-Finetuned/resolve/main/checkpoint-348/optimizer.pt
- Command line
-
hf download hf://SamChen888/Mistral-RDE-Finetuned/checkpoint-348/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/SamChen888/Mistral-RDE-Finetuned/resolve/main/checkpoint-348/optimizer.pt
168 MB
- Xet hash:
- cf3f836931892c440dd7a3db5e515f5d717293ff1dd7a64bd11542d269a61bd0
- Size of remote file:
- 168 MB
- SHA256:
- e3ec811984e978fd3fcf6f1d1df1c55ff9efc3d103e3f1a1453c1e260b537fcc
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