Instructions to use besimray/miner1_ba9938bd-5490-4a39-90ab-976131f92334_1730940656 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use besimray/miner1_ba9938bd-5490-4a39-90ab-976131f92334_1730940656 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/miner1_ba9938bd-5490-4a39-90ab-976131f92334_1730940656") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38a286c5f03e01354e0d7ab62521dd3ecd707da74a2faa11c492105dbb1c23ab
- Size of remote file:
- 6.71 kB
- SHA256:
- e559edc51f3857db921bfd5e63e3da7f2c9804b5e5b6b4ecb31e3205f6afb0c8
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