Instructions to use swlkk/gefr5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swlkk/gefr5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("swlkk/gefr5") model = AutoModelForMultimodalLM.from_pretrained("swlkk/gefr5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from swlkk/gefr5: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/swlkk/gefr5/resolve/main/tokenizer.json
- Command line
-
hf download hf://swlkk/gefr5/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/swlkk/gefr5/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- 56c0fa6cda1d4fc67d26339eff88af3a6245fc796e363fa0b4a8c019cf63b179
- Size of remote file:
- 32.2 MB
- SHA256:
- a43152a9caea76a7f589def6bbbe5d243bbded741fdb4e7e83c09796e39f8aab
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