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
Download training_args.bin from cbpuschmann/MiniLM-klimacoder_v0.4: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/cbpuschmann/MiniLM-klimacoder_v0.4/resolve/main/training_args.bin
- Command line
-
hf download hf://cbpuschmann/MiniLM-klimacoder_v0.4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cbpuschmann/MiniLM-klimacoder_v0.4/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- a18e5b5da76b19d4276adf7a096c9f22e8e0e785d648076fbbebd5c51f20fa1c
- Size of remote file:
- 5.3 kB
- SHA256:
- c99223f295eb8289ffaaffb2bf13f03bcb39de34bf1519699c18c5a5402376c6
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