Instructions to use pin/senda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pin/senda with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pin/senda")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pin/senda") model = AutoModelForSequenceClassification.from_pretrained("pin/senda") - Notebooks
- Google Colab
- Kaggle
Commit ·
851084b
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Parent(s): ded55ea
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 sha256:91d60466a8afae147292031007e0a96349e60f1d4dadbb6ce6fbcc49499c99bf
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size 442485820
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