Instructions to use Prience91/lora_sft_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prience91/lora_sft_output with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Prience91/lora_sft_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Prience91/lora_sft_output: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Prience91/lora_sft_output/resolve/main/tokenizer.json
- Command line
-
hf download hf://Prience91/lora_sft_output/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Prience91/lora_sft_output/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- d3f835122bddb470f53048ff36f1a5116791b8f3a003f9d17b3b03b0b81cc5fe
- Size of remote file:
- 11.4 MB
- SHA256:
- 3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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