Instructions to use BroAlanTaps/Stage1-PCC-Lite-64x with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BroAlanTaps/Stage1-PCC-Lite-64x with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BroAlanTaps/Stage1-PCC-Lite-64x")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("BroAlanTaps/Stage1-PCC-Lite-64x") model = AutoModelForMultimodalLM.from_pretrained("BroAlanTaps/Stage1-PCC-Lite-64x") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca7923294d60604e68d33ba1f1be748e61ee5771ac4a7f81adf88f8bf26d59d7
- Size of remote file:
- 3.1 GB
- SHA256:
- 5e05364d030f52a5198ba6e1b6b959bd4728fc80dc27fba5f843bca9b2ac89d8
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