Text Classification
Transformers
Safetensors
Persian
hes_shenaas_rizehpizeh
persian
farsi
emotion-classification
albert
small-model
custom_code
Instructions to use Reza2kn/Hes-Shenaas-RizehPizeh-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Reza2kn/Hes-Shenaas-RizehPizeh-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Reza2kn/Hes-Shenaas-RizehPizeh-v0.1", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("Reza2kn/Hes-Shenaas-RizehPizeh-v0.1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "bos_token": "[CLS]", | |
| "cls_token": "[CLS]", | |
| "eos_token": "[SEP]", | |
| "mask_token": "[MASK]", | |
| "max_length": 128, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "sep_token": "[SEP]", | |
| "stride": 0, | |
| "tokenizer_class": "TokenizersBackend", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "<unk>" | |
| } | |