Instructions to use eeeebbb2/58c184ac-ec68-4ded-81bd-1e193b6c2f3f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/58c184ac-ec68-4ded-81bd-1e193b6c2f3f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openlm-research/open_llama_3b") model = PeftModel.from_pretrained(base_model, "eeeebbb2/58c184ac-ec68-4ded-81bd-1e193b6c2f3f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b23c47b5bc9e61aee802a96530f5fa2965f9d55b7b155e7796567f36e8b831a
- Size of remote file:
- 204 MB
- SHA256:
- 41e62bb3bf983a1deab6a3a69af41b2c72a29bbe22153b4827868dbf56ecc94a
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