Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use scroobiustrip/topic-model-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scroobiustrip/topic-model-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scroobiustrip/topic-model-v3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scroobiustrip/topic-model-v3") model = AutoModelForSequenceClassification.from_pretrained("scroobiustrip/topic-model-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from scroobiustrip/topic-model-v3: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/scroobiustrip/topic-model-v3/resolve/main/training_args.bin
- Command line
-
hf download hf://scroobiustrip/topic-model-v3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/scroobiustrip/topic-model-v3/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 54c0b81aaf1fa3c0be1b435121fd78b9cddd5c32ce247c5efe0d55be5a87d125
- Size of remote file:
- 3.96 kB
- SHA256:
- 0a60b0cb9ea5618252db03e1b5e786978dc84deaf555c0538e5fd71b51f9c23e
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