Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Trained with AutoTrain
text-embeddings-inference
Instructions to use robo-noct/convo-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use robo-noct/convo-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="robo-noct/convo-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("robo-noct/convo-2") model = AutoModelForSequenceClassification.from_pretrained("robo-noct/convo-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aae2efefa27e30ccbb5037ff0c8d829f621d08ff76cf92918947090b8d03df52
- Size of remote file:
- 536 MB
- SHA256:
- a1f482aaad735073628d4af4328c049c511d6610d9781b10239ef004a1793c23
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