Instructions to use cardiffnlp/twitter-roberta-base-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/twitter-roberta-base-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/twitter-roberta-base-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment") - Inference
- Notebooks
- Google Colab
- Kaggle
used quantization onnx for easy use and low size
#21 opened 8 months ago
by
PraneshJs
Adding `safetensors` variant of this model
#19 opened about 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#18 opened about 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#17 opened over 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#16 opened over 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#15 opened over 1 year ago
by
SFconvertbot
Add tokenzier.json
#14 opened over 1 year ago
by
rcshubhadeep
Licence to use this model ?
#13 opened about 2 years ago
by
Lijoy
fix tokenizer load issue when rerun the example
👍 1
#11 opened almost 3 years ago
by
colzy
fix tokenizer load issue when rerun the example
#10 opened almost 3 years ago
by
colzy
Update metadata in README.md
#9 opened about 3 years ago
by
cm-cai
Update README.md
#7 opened about 3 years ago
by
nwagu
sage maker only giving top result
1
#5 opened over 3 years ago
by
gunjan0507
Adding `safetensors` variant of this model
#4 opened over 3 years ago
by
Narsil
How to trained a new model base on your model?
#3 opened over 3 years ago
by
longshared
Add YAML header
#2 opened over 3 years ago
by
christopher