Text Classification
Transformers
Joblib
Safetensors
multilingual
binary-classification
amis
agriculture
Instructions to use faodl/agri-wheat-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faodl/agri-wheat-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="faodl/agri-wheat-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("faodl/agri-wheat-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download transformer/tokenizer_config.json from faodl/agri-wheat-classifier: direct link, hf CLI and curl.
- Browser
- Download file 343 Bytes
-
https://huggingface.co/faodl/agri-wheat-classifier/resolve/main/transformer/tokenizer_config.json
- Command line
-
hf download hf://faodl/agri-wheat-classifier/transformer/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/faodl/agri-wheat-classifier/resolve/main/transformer/tokenizer_config.json
343 Bytes
| { | |
| "add_prefix_space": true, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "XLMRobertaTokenizer", | |
| "unk_token": "<unk>" | |
| } | |