Instructions to use jcbao77/bert-uncased-multi-task-fixed-weights-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcbao77/bert-uncased-multi-task-fixed-weights-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jcbao77/bert-uncased-multi-task-fixed-weights-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jcbao77/bert-uncased-multi-task-fixed-weights-mnli") model = AutoModelForSequenceClassification.from_pretrained("jcbao77/bert-uncased-multi-task-fixed-weights-mnli") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:eaf138b24164e25f5ef217cd7e3069a03f68b6169eadd04f7dacea9a3716f2f4
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size 437965908
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