Instructions to use m3hrdadfi/albert-fa-base-v2-ner-arman with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3hrdadfi/albert-fa-base-v2-ner-arman with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="m3hrdadfi/albert-fa-base-v2-ner-arman")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("m3hrdadfi/albert-fa-base-v2-ner-arman") model = AutoModelForTokenClassification.from_pretrained("m3hrdadfi/albert-fa-base-v2-ner-arman", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from m3hrdadfi/albert-fa-base-v2-ner-arman: direct link, hf CLI and curl.
- Browser
- Download file 72.4 MB
-
https://huggingface.co/m3hrdadfi/albert-fa-base-v2-ner-arman/resolve/main/tf_model.h5
- Command line
-
hf download hf://m3hrdadfi/albert-fa-base-v2-ner-arman/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/m3hrdadfi/albert-fa-base-v2-ner-arman/resolve/main/tf_model.h5
72.4 MB
- Xet hash:
- 8d5adc33e3bd4160ab035773e512ea03b7194c51287a5ad983e5c2bf606ed144
- Size of remote file:
- 72.4 MB
- SHA256:
- e70272c103aa1493666d23255deb2148d91709fd1c1938dc0302ff65ae2ba6bb
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