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 special_tokens_map.json from Intel/albert-base-v2-MRPC-int8-inc: direct link, hf CLI and curl.
- Browser
- Download file 173 Bytes
-
https://huggingface.co/Intel/albert-base-v2-MRPC-int8-inc/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://Intel/albert-base-v2-MRPC-int8-inc/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/Intel/albert-base-v2-MRPC-int8-inc/resolve/main/special_tokens_map.json
173 Bytes
| { | |
| "bos_token": "[CLS]", | |
| "cls_token": "[CLS]", | |
| "eos_token": "[SEP]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "<pad>", | |
| "sep_token": "[SEP]", | |
| "unk_token": "<unk>" | |
| } | |