Instructions to use flax-community/multilingual-vqa-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/multilingual-vqa-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="flax-community/multilingual-vqa-ft")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("flax-community/multilingual-vqa-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from flax-community/multilingual-vqa-ft: direct link, hf CLI and curl.
- Browser
- Download file 1.03 GB
-
https://huggingface.co/flax-community/multilingual-vqa-ft/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://flax-community/multilingual-vqa-ft/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/flax-community/multilingual-vqa-ft/resolve/main/flax_model.msgpack
1.03 GB
- Xet hash:
- dbeb0a0041c6c7889a7a0d88fa328e0f9b3f8a75ce651283b73809d70eb1d6cb
- Size of remote file:
- 1.03 GB
- SHA256:
- b48f39250228e1cb396b54ac66194fd31674b9d5f426a5e18108e2e562066107
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