Instructions to use erickdp/ssa_medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erickdp/ssa_medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="erickdp/ssa_medium")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("erickdp/ssa_medium") model = AutoModelForSequenceClassification.from_pretrained("erickdp/ssa_medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from erickdp/ssa_medium: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/erickdp/ssa_medium/resolve/main/training_args.bin
- Command line
-
hf download hf://erickdp/ssa_medium/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/erickdp/ssa_medium/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 1439be4a211a6a7f7c212b17bd7d1038ea9c1bc025491faf35c2f882c6c70c5d
- Size of remote file:
- 4.86 kB
- SHA256:
- b6da6b0bba047e6bd73d025e0661a9e1189536114d61e809777ad374e5625f0a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.