Text-to-Speech
Transformers
Safetensors
MLX
English
Hindi
llama
text-generation
tts
hindi
english
audio
speech
india
mlx-my-repo
text-generation-inference
4-bit precision
Instructions to use hashvibe007/Veena-mlx-4Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hashvibe007/Veena-mlx-4Bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="hashvibe007/Veena-mlx-4Bit")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("hashvibe007/Veena-mlx-4Bit") model = AutoModelForCausalLM.from_pretrained("hashvibe007/Veena-mlx-4Bit", device_map="auto") - MLX
How to use hashvibe007/Veena-mlx-4Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download hashvibe007/Veena-mlx-4Bit --local-dir Veena-mlx-4Bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer.json from hashvibe007/Veena-mlx-4Bit: direct link, hf CLI and curl.
- Browser
- Download file 22.9 MB
-
https://huggingface.co/hashvibe007/Veena-mlx-4Bit/resolve/main/tokenizer.json
- Command line
-
hf download hf://hashvibe007/Veena-mlx-4Bit/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hashvibe007/Veena-mlx-4Bit/resolve/main/tokenizer.json
22.9 MB
- Xet hash:
- 81300fbca49196ad6f0e8acca3dc0d9d81b046bddbd2309fa3535d71d67858be
- Size of remote file:
- 22.9 MB
- SHA256:
- c88f202c5216ed6485367f5a606093d54f9a89ef3c654001ccc10026fcd276f2
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