Instructions to use davanstrien/dataset-rows16-task-classifier-4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/dataset-rows16-task-classifier-4096 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davanstrien/dataset-rows16-task-classifier-4096", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/dataset-rows16-task-classifier-4096", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("davanstrien/dataset-rows16-task-classifier-4096", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __pycache__/modeling_encoder_seq_cls.cpython-312.pyc from davanstrien/dataset-rows16-task-classifier-4096: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/davanstrien/dataset-rows16-task-classifier-4096/resolve/main/__pycache__/modeling_encoder_seq_cls.cpython-312.pyc
- Command line
-
hf download hf://davanstrien/dataset-rows16-task-classifier-4096/__pycache__/modeling_encoder_seq_cls.cpython-312.pyc
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curl -L -o modeling_encoder_seq_cls.cpython-312.pyc https://huggingface.co/davanstrien/dataset-rows16-task-classifier-4096/resolve/main/__pycache__/modeling_encoder_seq_cls.cpython-312.pyc
3.38 kB
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