Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
Japanese
bert
Generated from Trainer
Instructions to use jarvisx17/japanese-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jarvisx17/japanese-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jarvisx17/japanese-sentiment-analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jarvisx17/japanese-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("jarvisx17/japanese-sentiment-analysis", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from jarvisx17/japanese-sentiment-analysis: direct link, hf CLI and curl.
- Browser
- Download file 605 Bytes
-
https://huggingface.co/jarvisx17/japanese-sentiment-analysis/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://jarvisx17/japanese-sentiment-analysis/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/jarvisx17/japanese-sentiment-analysis/resolve/main/tokenizer_config.json
605 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "do_subword_tokenize": true, | |
| "do_word_tokenize": true, | |
| "jumanpp_kwargs": null, | |
| "mask_token": "[MASK]", | |
| "mecab_kwargs": { | |
| "mecab_dic": "unidic_lite" | |
| }, | |
| "name_or_path": "/content/drive/MyDrive/Bert/autonlp-japanese-sentiment-59363", | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "special_tokens_map_file": null, | |
| "subword_tokenizer_type": "wordpiece", | |
| "sudachi_kwargs": null, | |
| "tokenizer_class": "BertJapaneseTokenizer", | |
| "tokenizer_file": null, | |
| "unk_token": "[UNK]", | |
| "word_tokenizer_type": "mecab" | |
| } | |