Text-to-Speech
Transformers
Safetensors
rumik_oss
text-generation
tts
indic
multilingual
mimi
speech
custom_code
Instructions to use rumik-ai/rumik-oss-1-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rumik-ai/rumik-oss-1-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="rumik-ai/rumik-oss-1-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("rumik-ai/rumik-oss-1-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d3a8b16b96fd341b3812cd4f7cc924de79cd0a5acc98baeca27fce236086797
- Size of remote file:
- 24.4 MB
- SHA256:
- c6be4b170e40e8887fed988cc813226c91763a4e07aafbd1976ffbc3e10a8ac9
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