Instructions to use 10ths/FADS_base_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 10ths/FADS_base_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="10ths/FADS_base_model", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("10ths/FADS_base_model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from 10ths/FADS_base_model: direct link, hf CLI and curl.
- Browser
- Download file 147 Bytes
-
https://huggingface.co/10ths/FADS_base_model/resolve/main/generation_config.json
- Command line
-
hf download hf://10ths/FADS_base_model/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/10ths/FADS_base_model/resolve/main/generation_config.json
147 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 1, | |
| "eos_token_id": 32000, | |
| "pad_token_id": 32000, | |
| "transformers_version": "4.41.2" | |
| } | |