Instructions to use gowitheflow/unsup-ensemble-s144-bs128-lr6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gowitheflow/unsup-ensemble-s144-bs128-lr6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gowitheflow/unsup-ensemble-s144-bs128-lr6")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("gowitheflow/unsup-ensemble-s144-bs128-lr6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gowitheflow/unsup-ensemble-s144-bs128-lr6: direct link, hf CLI and curl.
- Browser
- Download file 345 MB
-
https://huggingface.co/gowitheflow/unsup-ensemble-s144-bs128-lr6/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gowitheflow/unsup-ensemble-s144-bs128-lr6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gowitheflow/unsup-ensemble-s144-bs128-lr6/resolve/main/pytorch_model.bin
345 MB
- Xet hash:
- 80f1e7424db07e43f55dde3e65d62d11ea8158dca43ce6a2d338ea5aeeada52b
- Size of remote file:
- 345 MB
- SHA256:
- 15079f1b13a51dde3788fee59cdc04c3fb8cd726ff6800e9d1dd47909680b774
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