Text Classification
Transformers
PyTorch
ONNX
English
albert
text-classfication
int8
Intel® Neural Compressor
neural-compressor
PostTrainingStatic
Instructions to use INC4AI/albert-base-v2-sst2-int8-static-inc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use INC4AI/albert-base-v2-sst2-int8-static-inc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="INC4AI/albert-base-v2-sst2-int8-static-inc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("INC4AI/albert-base-v2-sst2-int8-static-inc") model = AutoModelForSequenceClassification.from_pretrained("INC4AI/albert-base-v2-sst2-int8-static-inc") - Notebooks
- Google Colab
- Kaggle
Align label mapping with sst2 config of glue dataset
#1
by lewtun HF Staff - opened
Hi there, your model is using a default label mapping. Accept this PR to align the label mapping with the sst2 config of the glue dataset this model was trained on. This will enable your model to be evaluated by Hugging Face's automatic model evaluator
xinhe changed pull request status to merged
hi, how can I accept?