Instructions to use Nargizi/screeve-postagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nargizi/screeve-postagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Nargizi/screeve-postagger")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Nargizi/screeve-postagger") model = AutoModelForTokenClassification.from_pretrained("Nargizi/screeve-postagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from Nargizi/screeve-postagger: direct link, hf CLI and curl.
- Browser
- Download file 161 Bytes
-
https://huggingface.co/Nargizi/screeve-postagger/resolve/main/generation_config.json
- Command line
-
hf download hf://Nargizi/screeve-postagger/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/Nargizi/screeve-postagger/resolve/main/generation_config.json
161 Bytes
| { | |
| "bos_token_id": 2, | |
| "decoder_start_token_id": 2, | |
| "eos_token_id": 3, | |
| "forced_eos_token_id": 3, | |
| "pad_token_id": 1, | |
| "transformers_version": "4.31.0" | |
| } | |