Instructions to use saadfr/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saadfr/lora_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("saadfr/lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from saadfr/lora_model: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/saadfr/lora_model/resolve/b5fe38d7abdad5f4e2275f6aa4a48de9531bea1a/tokenizer.json
- Command line
-
hf download hf://saadfr/lora_model@b5fe38d7abdad5f4e2275f6aa4a48de9531bea1a/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/saadfr/lora_model/resolve/b5fe38d7abdad5f4e2275f6aa4a48de9531bea1a/tokenizer.json
11.4 MB
- Xet hash:
- d8afa1f6f3ea3f16d98fce7895282a83c4eb38b30af190f43649a5188663f721
- Size of remote file:
- 11.4 MB
- SHA256:
- 091aa7594dc2fcfbfa06b9e3c22a5f0562ac14f30375c13af7309407a0e67b8a
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