Instructions to use Aynursusuz/CSM-TR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aynursusuz/CSM-TR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Aynursusuz/CSM-TR")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("Aynursusuz/CSM-TR") model = AutoModelForTextToWaveform.from_pretrained("Aynursusuz/CSM-TR") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Aynursusuz/CSM-TR with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Aynursusuz/CSM-TR to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Aynursusuz/CSM-TR to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Aynursusuz/CSM-TR to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Aynursusuz/CSM-TR", max_seq_length=2048, )
| { | |
| "attn_implementation": "sdpa", | |
| "bos_token_id": 128000, | |
| "depth_decoder_do_sample": true, | |
| "depth_decoder_temperature": 0.9, | |
| "do_sample": true, | |
| "max_length": 2048, | |
| "max_new_tokens": 125, | |
| "pad_token_id": 128256, | |
| "temperature": 0.9, | |
| "transformers_version": "4.52.3" | |
| } | |