Instructions to use muellerzr/sequence_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muellerzr/sequence_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="muellerzr/sequence_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("muellerzr/sequence_classification") model = AutoModelForSequenceClassification.from_pretrained("muellerzr/sequence_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from muellerzr/sequence_classification: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/muellerzr/sequence_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://muellerzr/sequence_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/muellerzr/sequence_classification/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 4cd590fd88b8cde149a2cf4473156934f0963a986dc8f53dd9537febc7b4b023
- Size of remote file:
- 268 MB
- SHA256:
- 85ef5333d84bf6bec0b4d2eae06451e3ad354900af9d5264664ae9dfc062e3fe
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