Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mp6kv/IQA_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mp6kv/IQA_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mp6kv/IQA_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mp6kv/IQA_classification") model = AutoModelForSequenceClassification.from_pretrained("mp6kv/IQA_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e438fcf8f9320c1bfdd208ab14ff3f006fc8ff848a435c21c488baabdb2a13dd
- Size of remote file:
- 3.06 kB
- SHA256:
- 2db6491923713f9f5c3d1bf57d42b5684b57d6f7f3bb30215b73f0e46d855041
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