Instructions to use hf-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from hf-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 208 Bytes
-
https://huggingface.co/hf-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/resolve/836d05f9be383db64b078f0efdaa4416f489ff66/generation_config.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration@836d05f9be383db64b078f0efdaa4416f489ff66/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/hf-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/resolve/836d05f9be383db64b078f0efdaa4416f489ff66/generation_config.json
208 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "output_attentions": false, | |
| "output_hidden_states": false, | |
| "transformers_version": "5.3.0.dev0", | |
| "use_cache": true | |
| } | |