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 training_args.bin from m3hrdadfi/albert-fa-base-v2-ner-arman: direct link, hf CLI and curl.
- Browser
- Download file 1.16 kB
-
https://huggingface.co/m3hrdadfi/albert-fa-base-v2-ner-arman/resolve/d415362a82652f7735e24fbaed17763f5f70ab63/training_args.bin
- Command line
-
hf download hf://m3hrdadfi/albert-fa-base-v2-ner-arman@d415362a82652f7735e24fbaed17763f5f70ab63/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/m3hrdadfi/albert-fa-base-v2-ner-arman/resolve/d415362a82652f7735e24fbaed17763f5f70ab63/training_args.bin
1.16 kB
- Xet hash:
- 6ea8eba21b4822a7ff265914c92763d116cef4704c527bb84ed41854c64dc04c
- Size of remote file:
- 1.16 kB
- SHA256:
- e1fee766bad731736629598303cc7b9eddef4384afb3735631e3cc67857bf0d8
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