Instructions to use aho-tai/PixtralEncoderDecoder-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aho-tai/PixtralEncoderDecoder-v0 with Transformers:
# Load model directly from transformers import VisionPixtralEncoderDecoder model = VisionPixtralEncoderDecoder.from_pretrained("aho-tai/PixtralEncoderDecoder-v0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e2c0f80a647a7a2d61c16c1e2e3cc6e81466c80f8e624729ef0517cfaba53ab
- Size of remote file:
- 2.81 GB
- SHA256:
- 46d0f12a41becf763629a128b3310725829fd63f8f8420568bdee03bafb28edb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.