Instructions to use anhuu/argument_classification_ibm_es_topic_topicconcept_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhuu/argument_classification_ibm_es_topic_topicconcept_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anhuu/argument_classification_ibm_es_topic_topicconcept_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anhuu/argument_classification_ibm_es_topic_topicconcept_bert") model = AutoModelForSequenceClassification.from_pretrained("anhuu/argument_classification_ibm_es_topic_topicconcept_bert") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:3cb61f51fe78d022c3fe067fbac65753b6c39532f869c6cdc159f5f972a5a5f4
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size 437962832
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