Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mpreda/test_dir_model3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpreda/test_dir_model3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mpreda/test_dir_model3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mpreda/test_dir_model3") model = AutoModelForSequenceClassification.from_pretrained("mpreda/test_dir_model3") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
ee7e279 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:dfd27eb4e63ec2e4ae3384f8b6916a5a65326a9db7ef14e1441eca7200030248
size 498618976
|