Instructions to use rreit/mistral-7B-StaproCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rreit/mistral-7B-StaproCoder with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "rreit/mistral-7B-StaproCoder") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rreit/mistral-7B-StaproCoder: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/rreit/mistral-7B-StaproCoder/resolve/main/training_args.bin
- Command line
-
hf download hf://rreit/mistral-7B-StaproCoder/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rreit/mistral-7B-StaproCoder/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 7f67878ebe94f6e7d43f7d7e6687019a7f618de7d2009c3bf06974a98fe6e953
- Size of remote file:
- 4.92 kB
- SHA256:
- a5639f6a95cfb8afa2357cc563d6a2d6f8cf2c577290a0f1ff28cd9991d54ff8
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