Instructions to use hellojimson/roberta-tagalog-base-ft-udpos213-ro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hellojimson/roberta-tagalog-base-ft-udpos213-ro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hellojimson/roberta-tagalog-base-ft-udpos213-ro")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hellojimson/roberta-tagalog-base-ft-udpos213-ro") model = AutoModelForTokenClassification.from_pretrained("hellojimson/roberta-tagalog-base-ft-udpos213-ro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train.args from hellojimson/roberta-tagalog-base-ft-udpos213-ro: direct link, hf CLI and curl.
- Browser
- Download file 109 Bytes
-
https://huggingface.co/hellojimson/roberta-tagalog-base-ft-udpos213-ro/resolve/main/train.args
- Command line
-
hf download hf://hellojimson/roberta-tagalog-base-ft-udpos213-ro/train.args
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curl -L -o train.args https://huggingface.co/hellojimson/roberta-tagalog-base-ft-udpos213-ro/resolve/main/train.args
109 Bytes
| udpos --learning_rate=5e-5 --eval_steps=1000 --per_device_batch_size=10 --max_steps=1000 --language_source=ro |