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:
- 377233011f1fa659a2b5599292c9eb4ce96cf9dc59dcd5d40d0cc27fc21a7861
- Size of remote file:
- 499 MB
- SHA256:
- 753b8dd6d7f1c4e6a77d33906990692966432f9336c029b7182c62cb78435e26
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