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:
- 8dd1668d802df448d3f7798784d799167f8713f1bd028fef94d9d46b3b0a7e1c
- Size of remote file:
- 336 MB
- SHA256:
- 16ebed32e35f7739ca95a7e68ac65884c95e08af87ef1a02bb0a63ec0e110dc1
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