Text Classification
setfit
TensorBoard
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use cbpuschmann/MiniLM-klimacoder_v0.4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use cbpuschmann/MiniLM-klimacoder_v0.4 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("cbpuschmann/MiniLM-klimacoder_v0.4") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use cbpuschmann/MiniLM-klimacoder_v0.4 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cbpuschmann/MiniLM-klimacoder_v0.4") 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] - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
runs/Dec02_13-27-59_r-cbpuschmann-sfautotrain-etooiy4s-3f6aa-552dm/events.out.tfevents.1733146081.r-cbpuschmann-sfautotrain-etooiy4s-3f6aa-552dm.223.0
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