Instructions to use codegood/Mistral_new_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use codegood/Mistral_new_data 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_new_data") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c911c7b51c6a565d67f54048385b7cc13ca21140a6dbc4ea7061c0586857fc9d
- Size of remote file:
- 4.88 GB
- SHA256:
- 55abb4473249fa9ab6e62d9deb7dc745f96bccd7f4f85ed780b02ad64016b30a
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