Instructions to use codegood/Mistral_instruct_latest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use codegood/Mistral_instruct_latest with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("filipealmeida/Mistral-7B-Instruct-v0.1-sharded") model = PeftModel.from_pretrained(base_model, "codegood/Mistral_instruct_latest") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from codegood/Mistral_instruct_latest: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/codegood/Mistral_instruct_latest/resolve/6f5c4028eea343b2ffc31f0cde236dafbd12d925/training_args.bin
- Command line
-
hf download hf://codegood/Mistral_instruct_latest@6f5c4028eea343b2ffc31f0cde236dafbd12d925/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codegood/Mistral_instruct_latest/resolve/6f5c4028eea343b2ffc31f0cde236dafbd12d925/training_args.bin
4.09 kB
- Xet hash:
- faaed97d9ef740995df09aedc64bd4a677f258d49f22898798ac2572c34c5279
- Size of remote file:
- 4.09 kB
- SHA256:
- 34bfb87bcd63286e412b8c4a791e932f8a87efc6d0850f0af666080c87ba8468
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