Text-to-Speech
Transformers
Safetensors
rumik_oss
text-generation
tts
indic
expressive
mimi
speech
custom_code
Instructions to use arvindcodex11/MYRA-oss-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arvindcodex11/MYRA-oss-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="arvindcodex11/MYRA-oss-1", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("arvindcodex11/MYRA-oss-1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download codec/preprocessor_config.json from arvindcodex11/MYRA-oss-1: direct link, hf CLI and curl.
- Browser
- Download file 234 Bytes
-
https://huggingface.co/arvindcodex11/MYRA-oss-1/resolve/main/codec/preprocessor_config.json
- Command line
-
hf download hf://arvindcodex11/MYRA-oss-1/codec/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/arvindcodex11/MYRA-oss-1/resolve/main/codec/preprocessor_config.json
234 Bytes
| { | |
| "chunk_length_s": null, | |
| "feature_extractor_type": "EncodecFeatureExtractor", | |
| "feature_size": 1, | |
| "overlap": null, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 24000 | |
| } | |