Instructions to use EshAhm/LoRa-Python2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EshAhm/LoRa-Python2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("EshAhm/LoRa-Python2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from EshAhm/LoRa-Python2: direct link, hf CLI and curl.
- Browser
- Download file 83.9 MB
-
https://huggingface.co/EshAhm/LoRa-Python2/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://EshAhm/LoRa-Python2/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/EshAhm/LoRa-Python2/resolve/main/adapter_model.safetensors
83.9 MB
- Xet hash:
- 07c78611012a75effab7e96be116f4a6bc9983cefad45d141442486971b2c73c
- Size of remote file:
- 83.9 MB
- SHA256:
- d0cb54926955f8465684c4f5a5d7fa4f8f6a6a2ecb1b624fdca9677961b29f12
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