Feature Extraction
Transformers
Safetensors
English
penguinvl_vision_encoder
multi-modal
large-language-model
vision-language-model
vision-encoder
custom_code
Instructions to use tencent/Penguin-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tencent/Penguin-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tencent/Penguin-Encoder", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tencent/Penguin-Encoder", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a346b895a7ace480cb3906d0b46b5e6cf5d3a35d698d8477b13d12df1bc28a3
- Size of remote file:
- 882 MB
- SHA256:
- 8c12c1beb59b8437b833884ab866628f5ddcf8fc83e3da2f7e10a9189c8d8aec
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