Instructions to use tarabukinivan/0a68d25b-d86b-42a5-93e9-49451351341f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/0a68d25b-d86b-42a5-93e9-49451351341f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "tarabukinivan/0a68d25b-d86b-42a5-93e9-49451351341f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f465a904770bd0a5f472f94d6978a5f0ed08d0f577749ec8a18d390eede41b5
- Size of remote file:
- 50.5 MB
- SHA256:
- b3f9e0c9ddf0c19d21538b0dcaa85caed1162f13837ecdc8df6fe456c7832492
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