Instructions to use babblebots/initial-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use babblebots/initial-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("babblebots/initial-model") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - setfit
How to use babblebots/initial-model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("babblebots/initial-model") - Notebooks
- Google Colab
- Kaggle
Add SetFit model
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by ishan - opened
README.md
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pipeline_tag: text-classification
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---
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# /var/folders/mt/147vhq713f1_gmbpccrp4hc00000gn/T/
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This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
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from setfit import SetFitModel
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# Download from Hub and run inference
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model = SetFitModel.from_pretrained("/var/folders/mt/147vhq713f1_gmbpccrp4hc00000gn/T/
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# Run inference
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preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])
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```
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pipeline_tag: text-classification
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---
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# /var/folders/mt/147vhq713f1_gmbpccrp4hc00000gn/T/tmpxtq1g279/ishan/initial-model
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This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
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from setfit import SetFitModel
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# Download from Hub and run inference
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model = SetFitModel.from_pretrained("/var/folders/mt/147vhq713f1_gmbpccrp4hc00000gn/T/tmpxtq1g279/ishan/initial-model")
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# Run inference
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preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])
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```
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