Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use cbpuschmann/klimacoder2_v0.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use cbpuschmann/klimacoder2_v0.3 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("cbpuschmann/klimacoder2_v0.3") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use cbpuschmann/klimacoder2_v0.3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cbpuschmann/klimacoder2_v0.3") 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 model_head.pkl from cbpuschmann/klimacoder2_v0.3: direct link, hf CLI and curl.
- Browser
- Download file 10.2 kB
-
https://huggingface.co/cbpuschmann/klimacoder2_v0.3/resolve/main/model_head.pkl
- Command line
-
hf download hf://cbpuschmann/klimacoder2_v0.3/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/cbpuschmann/klimacoder2_v0.3/resolve/main/model_head.pkl
10.2 kB
- Xet hash:
- 6e163dedaf3aa29f33fe25bf70445f1cfc7a501c650d12b9b94771ddcb557bcd
- Size of remote file:
- 10.2 kB
- SHA256:
- 4cfe02e4f5cc1a62fda3e2f12c230a1abbfd4e7405d80c5d5a85311d5db01abf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.