Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ultra-coder54732/MiniLM-prop-16-train-set with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ultra-coder54732/MiniLM-prop-16-train-set with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ultra-coder54732/MiniLM-prop-16-train-set")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ultra-coder54732/MiniLM-prop-16-train-set") model = AutoModelForSequenceClassification.from_pretrained("ultra-coder54732/MiniLM-prop-16-train-set", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from ultra-coder54732/MiniLM-prop-16-train-set: direct link, hf CLI and curl.
- Browser
- Download file 635 Bytes
-
https://huggingface.co/ultra-coder54732/MiniLM-prop-16-train-set/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://ultra-coder54732/MiniLM-prop-16-train-set/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ultra-coder54732/MiniLM-prop-16-train-set/resolve/main/tokenizer_config.json
635 Bytes
| { | |
| "batch_size": 16, | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": true, | |
| "mask_token": "[MASK]", | |
| "name_or_path": "microsoft/MiniLM-L12-H384-uncased", | |
| "never_split": null, | |
| "num_epochs": 10, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "special_tokens_map_file": "/root/.cache/huggingface/transformers/1e5909e4dfaa904617797ed35a6105a23daa56cbefca48fef329f772584699fb.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]", | |
| "use_cache": false, | |
| "verbose": true | |
| } | |