Instructions to use mateoguaman/vamos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mateoguaman/vamos with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("mateoguaman/vamos") model = AutoModelForMultimodalLM.from_pretrained("mateoguaman/vamos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from mateoguaman/vamos: direct link, hf CLI and curl.
- Browser
- Download file 34.6 MB
-
https://huggingface.co/mateoguaman/vamos/resolve/main/tokenizer.json
- Command line
-
hf download hf://mateoguaman/vamos/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mateoguaman/vamos/resolve/main/tokenizer.json
34.6 MB
- Xet hash:
- 1d4ec5ac87cdc9032af84e422434305926635b839ee8e1a8eacb5f41fb3d581d
- Size of remote file:
- 34.6 MB
- SHA256:
- 172fab587d68c56b63eb3620057c62dfd15e503079ff7fce584692e3fd5bf4da
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