Instructions to use heavyhelium/electra-small-touche-rawplusctx-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heavyhelium/electra-small-touche-rawplusctx-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="heavyhelium/electra-small-touche-rawplusctx-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("heavyhelium/electra-small-touche-rawplusctx-binary") model = AutoModelForSequenceClassification.from_pretrained("heavyhelium/electra-small-touche-rawplusctx-binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa45925d3e7980160516b5fbc38151d251f687998a182254ce322e7956d226fd
- Size of remote file:
- 5.46 kB
- SHA256:
- cc5901dd89bc4001eae56c39d102ead320c920268eead43685a352ba001b4959
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.