Instructions to use besimray/miner_id_1_383a850e-bb15-45a2-8f4b-fc96eb001a74_1729770655 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use besimray/miner_id_1_383a850e-bb15-45a2-8f4b-fc96eb001a74_1729770655 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "besimray/miner_id_1_383a850e-bb15-45a2-8f4b-fc96eb001a74_1729770655") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5c62b377d9a863c22793d5725c1657ef584a54ed95c8543274faa52f4998a73
- Size of remote file:
- 22.6 MB
- SHA256:
- 676d4ab8c76c93e64d02aab93625bc6aef38f8777aa2ac44e788c4c1c4138494
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