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 pytorch_model.bin from scroobiustrip/topic-model-v3: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/scroobiustrip/topic-model-v3/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://scroobiustrip/topic-model-v3@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/scroobiustrip/topic-model-v3/resolve/refs%2Fpr%2F2/pytorch_model.bin
1.11 GB
- Xet hash:
- 54d7076a96e45a80d65b3245035b9a1861021a1ba82ff77638d491ec2b13700e
- Size of remote file:
- 1.11 GB
- SHA256:
- 4020de207e47ab32c5cf64289f84403ff9677c1af9a6c11319c8f443b94c6050
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