Instructions to use tyasmul/4be2b827-41b0-4608-a605-3bc499df4c51 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tyasmul/4be2b827-41b0-4608-a605-3bc499df4c51 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "tyasmul/4be2b827-41b0-4608-a605-3bc499df4c51") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19411a6283ab153f741b1fe5a99b3a7ccdbe396d05038178dc486f236801b83e
- Size of remote file:
- 168 MB
- SHA256:
- 3ef8598a98ab84fdde3299cfb08f458fe6dca17bbc01c53d6ca2038f1fbc410c
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