Instructions to use gszabo/test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/test1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/test1") model = AutoModelForMaskedLM.from_pretrained("gszabo/test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from gszabo/test1: direct link, hf CLI and curl.
- Browser
- Download file 243 Bytes
-
https://huggingface.co/gszabo/test1/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://gszabo/test1/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/gszabo/test1/resolve/main/tokenizer_config.json
243 Bytes
| { | |
| "name_or_path": "gszabo/test1", | |
| "special_tokens_map_file": "/root/.cache/huggingface/hub/models--gszabo--test1/snapshots/6f8df0182582a5d3ae2d140e30c94b8bf36bc3f4/special_tokens_map.json", | |
| "tokenizer_class": "PreTrainedTokenizerFast" | |
| } | |