Instructions to use memegpt/blip2_endpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use memegpt/blip2_endpoint with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" 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("image-to-text", model="memegpt/blip2_endpoint")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("memegpt/blip2_endpoint") model = AutoModelForMultimodalLM.from_pretrained("memegpt/blip2_endpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from memegpt/blip2_endpoint: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/memegpt/blip2_endpoint/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
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hf download hf://memegpt/blip2_endpoint@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/memegpt/blip2_endpoint/resolve/refs%2Fpr%2F1/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.