Instructions to use ArmelRandy/mistral-7b-100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ArmelRandy/mistral-7b-100 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, "ArmelRandy/mistral-7b-100") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19131bad03b28c37f6b2972661557919134e43ad0d5ec1f5c66b087a99547467
- Size of remote file:
- 75.7 MB
- SHA256:
- 76da0c6b9dd69569b8d314c2c8a635389191be1ba5824bd84f4ef231bcce9b95
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