Instructions to use researchworkai/Sentiment-roBERTa-Twitter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use researchworkai/Sentiment-roBERTa-Twitter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="researchworkai/Sentiment-roBERTa-Twitter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("researchworkai/Sentiment-roBERTa-Twitter") model = AutoModelForSequenceClassification.from_pretrained("researchworkai/Sentiment-roBERTa-Twitter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from researchworkai/Sentiment-roBERTa-Twitter: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/researchworkai/Sentiment-roBERTa-Twitter/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://researchworkai/Sentiment-roBERTa-Twitter/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/researchworkai/Sentiment-roBERTa-Twitter/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- ed1353e4bbb4ff858cb9bd80bbddbb297ae5590a3c04b2b3ce617dad898ae324
- Size of remote file:
- 499 MB
- SHA256:
- a4d892ae550c152fd6175b7be9841cd9d3509ae80ea4b0aefe28ba41ea610d4d
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