Text Classification
Transformers
ONNX
Safetensors
English
Portuguese
bert
classification
questioning
directed
generic
text-embeddings-inference
Instructions to use cnmoro/bert-tiny-question-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cnmoro/bert-tiny-question-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cnmoro/bert-tiny-question-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cnmoro/bert-tiny-question-classifier") model = AutoModelForSequenceClassification.from_pretrained("cnmoro/bert-tiny-question-classifier") - Notebooks
- Google Colab
- Kaggle
File size: 310 Bytes
3075b79 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"modes": [
"fp16",
"q8",
"int8",
"uint8",
"q4",
"q4f16",
"bnb4"
],
"per_channel": true,
"reduce_range": true,
"block_size": null,
"is_symmetric": true,
"accuracy_level": null,
"quant_type": 1,
"op_block_list": null
} |