Instructions to use boronbrown48/topic_otherTopics_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boronbrown48/topic_otherTopics_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boronbrown48/topic_otherTopics_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boronbrown48/topic_otherTopics_v2") model = AutoModelForSequenceClassification.from_pretrained("boronbrown48/topic_otherTopics_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from boronbrown48/topic_otherTopics_v2: direct link, hf CLI and curl.
- Browser
- Download file 421 MB
-
https://huggingface.co/boronbrown48/topic_otherTopics_v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://boronbrown48/topic_otherTopics_v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/boronbrown48/topic_otherTopics_v2/resolve/main/pytorch_model.bin
421 MB
- Xet hash:
- ed55fcb383a548e206d81438322ac0ce8078577b1445f82518aec2bcea56b8e3
- Size of remote file:
- 421 MB
- SHA256:
- 733d274535cce7c66dc568e89649ffaf819024a5de17f7b12c43ed4f6191f449
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