Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Intel/MiniLM-L12-H384-uncased-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/MiniLM-L12-H384-uncased-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/MiniLM-L12-H384-uncased-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/MiniLM-L12-H384-uncased-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Intel/MiniLM-L12-H384-uncased-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Intel/MiniLM-L12-H384-uncased-mrpc: direct link, hf CLI and curl.
- Browser
- Download file 532 Bytes
-
https://huggingface.co/Intel/MiniLM-L12-H384-uncased-mrpc/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Intel/MiniLM-L12-H384-uncased-mrpc/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Intel/MiniLM-L12-H384-uncased-mrpc/resolve/main/tokenizer_config.json
532 Bytes
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": "/home2/xinhe/.cache/huggingface/transformers/1e5909e4dfaa904617797ed35a6105a23daa56cbefca48fef329f772584699fb.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "name_or_path": "microsoft/MiniLM-L12-H384-uncased", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |