Instructions to use vicd/sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vicd/sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vicd/sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vicd/sentiment") model = AutoModelForSequenceClassification.from_pretrained("vicd/sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
da117e2
1
Parent(s): 2f5f74d
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:8d326fb7e71416fd3b734c8810e03eecb461c78ead78149151165bc545be7b53
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size 498595901
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