Text Classification
Transformers
Safetensors
English
bert
feature-extraction
answer-evaluation
evaluation-metrics
completeness
long-form-qa
question-answering
regression
custom_code
text-embeddings-inference
Instructions to use egcortes/qa-completeness-regressor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use egcortes/qa-completeness-regressor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="egcortes/qa-completeness-regressor", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("egcortes/qa-completeness-regressor", trust_remote_code=True) model = AutoModel.from_pretrained("egcortes/qa-completeness-regressor", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |