Instructions to use cimol/85d5500f-577e-4c16-be0b-9b41451bd06e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/85d5500f-577e-4c16-be0b-9b41451bd06e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b") model = PeftModel.from_pretrained(base_model, "cimol/85d5500f-577e-4c16-be0b-9b41451bd06e") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from cimol/85d5500f-577e-4c16-be0b-9b41451bd06e: direct link, hf CLI and curl.
- Browser
- Download file 671 MB
-
https://huggingface.co/cimol/85d5500f-577e-4c16-be0b-9b41451bd06e/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://cimol/85d5500f-577e-4c16-be0b-9b41451bd06e/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/cimol/85d5500f-577e-4c16-be0b-9b41451bd06e/resolve/main/adapter_model.safetensors
671 MB
- Xet hash:
- 17e1e3e1c94bc13af1602527d5e1506ff49caf70678c18e4c8ae02b6d38b58f5
- Size of remote file:
- 671 MB
- SHA256:
- 21e87446c2bb239411818d6018d7bf0ad5759fda0ac69d39ab88a2b174efeef8
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