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:
- f124f76df259ef485678cdd6b600ebdc07d429e540a282016f5722675d95ddca
- Size of remote file:
- 6.71 kB
- SHA256:
- 1ae69bdb3600b82d4b8cf2faffbefda81879cf7e73976942e9722a8e0e300ba3
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