Text Classification
Transformers
PyTorch
sentiment-head
feature-extraction
sentiment-analysis
openai-embeddings
custom_code
Instructions to use marcovise/TextEmbedding3SmallSentimentHead with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcovise/TextEmbedding3SmallSentimentHead with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcovise/TextEmbedding3SmallSentimentHead", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("marcovise/TextEmbedding3SmallSentimentHead", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
Browse filesThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to `pytorch_model.bin` but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
- model.safetensors +3 -0
model.safetensors
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oid sha256:f987a0a26a5a516eeff9da13e1e5256ac830a2bb768e739ae767b4b3f7376fdc
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size 1577316
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