Instructions to use avichr/heBERT_sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avichr/heBERT_sentiment_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="avichr/heBERT_sentiment_analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("avichr/heBERT_sentiment_analysis") model = AutoModelForSequenceClassification.from_pretrained("avichr/heBERT_sentiment_analysis") - Inference
- Notebooks
- Google Colab
- Kaggle
Add TF weights
#1
by joaogante - opened
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:58b54952741afb0e662fb6e6b4b37206443477292f2ce0bd7623053fa9fc3f26
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size 438226204
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