Instructions to use hfl/rbt4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/rbt4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/rbt4")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/rbt4") model = AutoModelForMaskedLM.from_pretrained("hfl/rbt4") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 0d7172c
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:c6c65653ad09fa8fbc9411225566b255394c1ea3de4d3c3f060c4d23b49299a1
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size 182352065
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