Instructions to use ishan/bert-base-uncased-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ishan/bert-base-uncased-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ishan/bert-base-uncased-mnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ishan/bert-base-uncased-mnli") model = AutoModelForSequenceClassification.from_pretrained("ishan/bert-base-uncased-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 743d0b0
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 sha256:471fb2615bb190cecc9d3790950ac3a2e1f40d59a143d9ded4a56ea275792a42
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size 437945404
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