Instructions to use peeache/FL2_VQA_64_128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peeache/FL2_VQA_64_128 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("peeache/FL2_VQA_64_128", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from peeache/FL2_VQA_64_128: direct link, hf CLI and curl.
- Browser
- Download file 101 MB
-
https://huggingface.co/peeache/FL2_VQA_64_128/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://peeache/FL2_VQA_64_128/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/peeache/FL2_VQA_64_128/resolve/main/adapter_model.safetensors
101 MB
- Xet hash:
- 781ab39e472d4e3f74cf3d5542e5cace80c5d6bf195d9b3ad7a71c09e6928192
- Size of remote file:
- 101 MB
- SHA256:
- fc279739b4e769ed4d92f3f83b733fcc10ecd39dc2e8a287f4cb53e148f52c5e
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