Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use agi-css/distilroberta-base-mic-nlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agi-css/distilroberta-base-mic-nlp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agi-css/distilroberta-base-mic-nlp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agi-css/distilroberta-base-mic-nlp") model = AutoModelForSequenceClassification.from_pretrained("agi-css/distilroberta-base-mic-nlp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e06dca304c5fe4b0adce0101b4118a77432344c0c7d690d6ec2e4db810f7ac12
- Size of remote file:
- 3.06 kB
- SHA256:
- 97e75c7463aa97019c3c72dc2e2a7290238154152fd656a23fbdf217fac70cee
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