Instructions to use LeonKogler/trainedModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeonKogler/trainedModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LeonKogler/trainedModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LeonKogler/trainedModel") model = AutoModelForSequenceClassification.from_pretrained("LeonKogler/trainedModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from LeonKogler/trainedModel: direct link, hf CLI and curl.
- Browser
- Download file 26 Bytes
-
https://huggingface.co/LeonKogler/trainedModel/resolve/main/added_tokens.json
- Command line
-
hf download hf://LeonKogler/trainedModel/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/LeonKogler/trainedModel/resolve/main/added_tokens.json
26 Bytes
| { | |
| "[MASK]": 128000 | |
| } | |