Visual Question Answering
Transformers
Safetensors
English
internvl_chat
feature-extraction
custom_code
Instructions to use SakanaAI/TAID-VLM-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SakanaAI/TAID-VLM-2B with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="SakanaAI/TAID-VLM-2B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SakanaAI/TAID-VLM-2B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from SakanaAI/TAID-VLM-2B: direct link, hf CLI and curl.
- Browser
- Download file 1.48 MB
-
https://huggingface.co/SakanaAI/TAID-VLM-2B/resolve/main/tokenizer.model
- Command line
-
hf download hf://SakanaAI/TAID-VLM-2B/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/SakanaAI/TAID-VLM-2B/resolve/main/tokenizer.model
1.48 MB
- Xet hash:
- eb88de5faa9e82368b3bee26636575e1c4b57b4e27ceaf70e456ac377aacd8e3
- Size of remote file:
- 1.48 MB
- SHA256:
- f868398fc4e05ee1e8aeba95ddf18ddcc45b8bce55d5093bead5bbf80429b48b
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