Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ltuzova/amazon_helpfulness_classification_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltuzova/amazon_helpfulness_classification_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ltuzova/amazon_helpfulness_classification_roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ltuzova/amazon_helpfulness_classification_roberta") model = AutoModelForSequenceClassification.from_pretrained("ltuzova/amazon_helpfulness_classification_roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ltuzova/amazon_helpfulness_classification_roberta: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/ltuzova/amazon_helpfulness_classification_roberta/resolve/main/training_args.bin
- Command line
-
hf download hf://ltuzova/amazon_helpfulness_classification_roberta/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ltuzova/amazon_helpfulness_classification_roberta/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 483ed2b04679f6d6b64637ece1dffafc5436428bc7d5a27fb4530197ce6194b0
- Size of remote file:
- 4.98 kB
- SHA256:
- 6ef08575d4064fbcbb1604670b47960ce9ddba4b82b16ed3d958aed5395de4e7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.