Instructions to use alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f: direct link, hf CLI and curl.
- Browser
- Download file 296 MB
-
https://huggingface.co/alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f/resolve/main/adapter_model.bin
- Command line
-
hf download hf://alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/alchemist69/4af9ed1e-bd3a-483b-889b-badf5ae1616f/resolve/main/adapter_model.bin
296 MB
- Xet hash:
- 5115596d0f336f1845677ce16b7a0b85aef26b216b17098c6d76bd0d0d18b019
- Size of remote file:
- 296 MB
- SHA256:
- e186c659f73b5cb1b1cb93284ccfc6aa2e3242f17dd2dc99fb521c1d5034f8da
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