Token Classification
Transformers
Safetensors
Persian
bert
feature-extraction
persian
word-importance
salience
dhh
asr-evaluation
ace-metric
distillation
Instructions to use Reza2kn/ShenavaSanj-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Reza2kn/ShenavaSanj-v1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Reza2kn/ShenavaSanj-v1.0")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Reza2kn/ShenavaSanj-v1.0") model = AutoModel.from_pretrained("Reza2kn/ShenavaSanj-v1.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a97e71cbf99b90d9452b4728b303d5984eb6df7ac52d441e6aacf97cfcd325f4
- Size of remote file:
- 4.88 kB
- SHA256:
- 572ec024a79595aa1ec60c933d02f283a72fd1e4690b1fa61fc980ba44f0b3b2
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