Instructions to use peeache/FL2_VQA_128_256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peeache/FL2_VQA_128_256 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("peeache/FL2_VQA_128_256", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from peeache/FL2_VQA_128_256: direct link, hf CLI and curl.
- Browser
- Download file 202 MB
-
https://huggingface.co/peeache/FL2_VQA_128_256/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://peeache/FL2_VQA_128_256/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/peeache/FL2_VQA_128_256/resolve/main/adapter_model.safetensors
202 MB
- Xet hash:
- 17851436171746e6c478a98ac761dca3ca21749c2506aa3f043533946dfdfa48
- Size of remote file:
- 202 MB
- SHA256:
- 3a547ccee4b48376d2a2ebd2c8d79bb16fb822fa3f6b0a443c8878ad4a2862b3
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