Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AndreiUrsu/TweetRobertaNewDataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndreiUrsu/TweetRobertaNewDataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AndreiUrsu/TweetRobertaNewDataset")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AndreiUrsu/TweetRobertaNewDataset") model = AutoModelForSequenceClassification.from_pretrained("AndreiUrsu/TweetRobertaNewDataset", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AndreiUrsu/TweetRobertaNewDataset: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/AndreiUrsu/TweetRobertaNewDataset/resolve/main/training_args.bin
- Command line
-
hf download hf://AndreiUrsu/TweetRobertaNewDataset/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AndreiUrsu/TweetRobertaNewDataset/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- c2056cee3778ddc419d99e2c42be6ceae31b260abb89dc7c1db8397104514546
- Size of remote file:
- 4.98 kB
- SHA256:
- 9d6bd02c849d590f036c14585badcd87cde8ee9210974d1e8f725799e79ba7be
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