Instructions to use boronbrown48/1_model_topic_classification_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boronbrown48/1_model_topic_classification_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boronbrown48/1_model_topic_classification_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boronbrown48/1_model_topic_classification_v2") model = AutoModelForSequenceClassification.from_pretrained("boronbrown48/1_model_topic_classification_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from boronbrown48/1_model_topic_classification_v2: direct link, hf CLI and curl.
- Browser
- Download file 421 MB
-
https://huggingface.co/boronbrown48/1_model_topic_classification_v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://boronbrown48/1_model_topic_classification_v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/boronbrown48/1_model_topic_classification_v2/resolve/main/pytorch_model.bin
421 MB
- Xet hash:
- 314e894cfaefeb6136e75f6953fcd52365db6968de9a3e8380d8f89766ad43e6
- Size of remote file:
- 421 MB
- SHA256:
- 2bfdf729469633066acf3794285855783b2c2a303382c51ee73bc3d82e3236ec
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