Instructions to use jsaurabh/mistral_finance_alpaca_finetuned_tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jsaurabh/mistral_finance_alpaca_finetuned_tmp 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, "jsaurabh/mistral_finance_alpaca_finetuned_tmp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d7d8b43784a16638d0c2e366fac4742a38c24171353b27e78fd6cc057581c3a
- Size of remote file:
- 27.4 MB
- SHA256:
- cee79b384a4238ab3d3ef73dff3206c608dea6272468d6c8bd556d6eea08b406
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