Instructions to use hkondle/CapstoneMainModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hkondle/CapstoneMainModel 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="hkondle/CapstoneMainModel")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hkondle/CapstoneMainModel") model = AutoModelForMultimodalLM.from_pretrained("hkondle/CapstoneMainModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c8f4a025d49fb2be899e37594f2e0774423b5ecd5635c1dd4fa0300c32e29a6
- Size of remote file:
- 990 MB
- SHA256:
- 2c079de1c52f8650f54c7b368e66de66bd0d1cf0bab76b0087f6c409d7aea8c0
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