Instructions to use nchervyakov/super-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nchervyakov/super-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nchervyakov/super-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nchervyakov/super-model") model = AutoModelForSequenceClassification.from_pretrained("nchervyakov/super-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from nchervyakov/super-model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/nchervyakov/super-model/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://nchervyakov/super-model/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/nchervyakov/super-model/resolve/main/flax_model.msgpack
438 MB
- Xet hash:
- 840b548b3effeda84f5b0876040f6be50d0eb8960e9fae4c130d55fb6292830f
- Size of remote file:
- 438 MB
- SHA256:
- d93ccc6caa234156d7a63cffd4b968fa7d6a47f544bded1e8f040045f1334cf9
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