Instructions to use alessiodecastro/LoRA_adapters_Pixtral_12B_FineTuningRecaptcha_promptv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alessiodecastro/LoRA_adapters_Pixtral_12B_FineTuningRecaptcha_promptv2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("alessiodecastro/LoRA_adapters_Pixtral_12B_FineTuningRecaptcha_promptv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from alessiodecastro/LoRA_adapters_Pixtral_12B_FineTuningRecaptcha_promptv2: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/alessiodecastro/LoRA_adapters_Pixtral_12B_FineTuningRecaptcha_promptv2/resolve/main/tokenizer.json
- Command line
-
hf download hf://alessiodecastro/LoRA_adapters_Pixtral_12B_FineTuningRecaptcha_promptv2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/alessiodecastro/LoRA_adapters_Pixtral_12B_FineTuningRecaptcha_promptv2/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- f9060b98d63313929e41d1c9761527ef3848743ad6833a0d50f203d883dc6dc3
- Size of remote file:
- 17.1 MB
- SHA256:
- 84f33e6f52b2833e8cc17229af8eea363f640a898f19a48184a2c7f6f5a88337
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.