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 training_args.bin from boronbrown48/1_model_topic_classification_v2: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/boronbrown48/1_model_topic_classification_v2/resolve/main/training_args.bin
- Command line
-
hf download hf://boronbrown48/1_model_topic_classification_v2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/boronbrown48/1_model_topic_classification_v2/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 1ef6fd7674a1e50d2bb7a66edb5b0819c105c605da0e1006d881802baecb3933
- Size of remote file:
- 2.86 kB
- SHA256:
- 953c7c41a6f86fc0e268eb7eaa150fc2c04be26345d04de09595b27a863b7e93
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