Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use chunwoolee0/seqcls_mrpc_bert_base_uncased_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chunwoolee0/seqcls_mrpc_bert_base_uncased_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chunwoolee0/seqcls_mrpc_bert_base_uncased_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chunwoolee0/seqcls_mrpc_bert_base_uncased_model") model = AutoModelForSequenceClassification.from_pretrained("chunwoolee0/seqcls_mrpc_bert_base_uncased_model") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
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 sha256:00f5cfdb24c4082a37c6c61bd47ecf7f28191b83eb4e4a5e10156fa34d968f74
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size 437962832
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