Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Hemg/twitter-sentiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hemg/twitter-sentiments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hemg/twitter-sentiments")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hemg/twitter-sentiments") model = AutoModelForSequenceClassification.from_pretrained("Hemg/twitter-sentiments", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Hemg/twitter-sentiments: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/Hemg/twitter-sentiments/resolve/main/training_args.bin
- Command line
-
hf download hf://Hemg/twitter-sentiments/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Hemg/twitter-sentiments/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- c4ac1063231fee30e784e82e009640aa5fed68cb91d49e43ae817ff397d56074
- Size of remote file:
- 4.92 kB
- SHA256:
- cd80b33edde27a571d6b2262f03ab2f0158b3156199eb8386a06c97df17c4a6c
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