Token Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use Osquery/1a5e2b8e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Osquery/1a5e2b8e with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Osquery/1a5e2b8e")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Osquery/1a5e2b8e") model = AutoModelForTokenClassification.from_pretrained("Osquery/1a5e2b8e", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train.args from Osquery/1a5e2b8e: direct link, hf CLI and curl.
- Browser
- Download file 117 Bytes
-
https://huggingface.co/Osquery/1a5e2b8e/resolve/main/train.args
- Command line
-
hf download hf://Osquery/1a5e2b8e/train.args
-
curl -L -o train.args https://huggingface.co/Osquery/1a5e2b8e/resolve/main/train.args
117 Bytes
| udpos --learning_rate=5e-5 --eval_steps=1000 --per_device_batch_size=10 --max_steps=1000 --multi --language_source te |