Instructions to use unum-cloud/uform-vl-english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unum-cloud/uform-vl-english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="unum-cloud/uform-vl-english")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unum-cloud/uform-vl-english", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload 2 files
Browse files- config.json +1 -0
- weight.pt +3 -0
config.json
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{"img_encoder": {"backbone": "deit3_base_patch16_224_in21ft1k", "dim": 768, "backbone_type": "vit", "pooling": "cls", "output_dim": 256}, "text_encoder": {"backbone": "google/bert_uncased_L-4_H-768_A-12", "backbone_type": "bert", "unimodal_n_layers": 2, "dim": 768, "pooling": "cls", "context_dim": 768, "output_dim": 256, "head_one_neuron": false}}
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weight.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:c5ea529a78aa90c8c98e616d2ffb40fe68efd97e2189a9132cc84cc6b9632f81
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size 572596251
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