Instructions to use M-CLIP/M-BERT-Base-69 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M-CLIP/M-BERT-Base-69 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="M-CLIP/M-BERT-Base-69")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("M-CLIP/M-BERT-Base-69") model = AutoModel.from_pretrained("M-CLIP/M-BERT-Base-69") - Notebooks
- Google Colab
- Kaggle
Commit ·
e5bf285
1
Parent(s): a7ec011
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:165a9459d8d1773a8c626053a0f889a02350f25fca7f89384e6060f3c3f2f18f
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size 711420911
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