Text Classification
Transformers
Safetensors
Telugu
chandassu_poem_cnn
feature-extraction
telugu
poetry
poetic-meter
cnn
eight-class
custom_code
Instructions to use sprx7767/chandassu-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sprx7767/chandassu-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sprx7767/chandassu-recognition", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sprx7767/chandassu-recognition", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from sprx7767/chandassu-recognition: direct link, hf CLI and curl.
- Browser
- Download file 205 Bytes
-
https://huggingface.co/sprx7767/chandassu-recognition/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://sprx7767/chandassu-recognition/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/sprx7767/chandassu-recognition/resolve/main/tokenizer_config.json
205 Bytes
| { | |
| "auto_map": { | |
| "AutoTokenizer": [ | |
| "hf_poem.ChandassuPoemTokenizer", | |
| null | |
| ] | |
| }, | |
| "model_max_length": 512, | |
| "padding_side": "right", | |
| "tokenizer_class": "ChandassuPoemTokenizer" | |
| } | |