Text Classification
Transformers
PyTorch
English
albert
text-classfication
nlp
neural-compressor
PostTrainingsDynamic
int8
Intel® Neural Compressor
Instructions to use Intel/albert-base-v2-MRPC-int8-inc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/albert-base-v2-MRPC-int8-inc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/albert-base-v2-MRPC-int8-inc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/albert-base-v2-MRPC-int8-inc") model = AutoModelForSequenceClassification.from_pretrained("Intel/albert-base-v2-MRPC-int8-inc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Intel/albert-base-v2-MRPC-int8-inc: direct link, hf CLI and curl.
- Browser
- Download file 45 MB
-
https://huggingface.co/Intel/albert-base-v2-MRPC-int8-inc/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Intel/albert-base-v2-MRPC-int8-inc/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Intel/albert-base-v2-MRPC-int8-inc/resolve/main/pytorch_model.bin
45 MB
- Xet hash:
- 8d0e7d5d65b7abf08a3877ebabed471f085787590a8a5198a1aa812ee9c8113a
- Size of remote file:
- 45 MB
- SHA256:
- 5f2652f3e1a508560f8644a21effc4c2868a1638c2286a1aea17fb8bd5c21087
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