Instructions to use Ojeda01/bert_base_cased_MultiClass_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ojeda01/bert_base_cased_MultiClass_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ojeda01/bert_base_cased_MultiClass_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ojeda01/bert_base_cased_MultiClass_v2") model = AutoModelForSequenceClassification.from_pretrained("Ojeda01/bert_base_cased_MultiClass_v2") - 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 sha256:8ae5bcd723f31255f017a1a9a84130e776eab2c04f318298cbe46ea4ae03c31a
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size 433324168
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