Instructions to use EdBergJr/Llama32B_Baha_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use EdBergJr/Llama32B_Baha_3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "EdBergJr/Llama32B_Baha_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91a38e94549cf7c7a99560b12fe8177dbb844acd47c1a52e07b45ef4d9b7a5aa
- Size of remote file:
- 5.5 kB
- SHA256:
- ccfa16e60fc9bbcaec7a2778c232c0e0d856497fa00404e2b82b3382db947ac6
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