Instructions to use kkatiz/THAI-BLIP-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kkatiz/THAI-BLIP-2 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="kkatiz/THAI-BLIP-2")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("kkatiz/THAI-BLIP-2") model = AutoModelForMultimodalLM.from_pretrained("kkatiz/THAI-BLIP-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 906df9e322d44acbfd6462093e679ac82d8cc681841c8d4c4c3b078b51b6063a
- Size of remote file:
- 604 MB
- SHA256:
- 0d52f791c6ad45517a2f3443ec41ec4fc0cc36574e35eb9166bcb183a20009fd
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