Text-to-Speech
Transformers
Safetensors
English
llama
text-generation
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use unsloth/orpheus-3b-0.1-ft-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/orpheus-3b-0.1-ft-bnb-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="unsloth/orpheus-3b-0.1-ft-bnb-4bit")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("unsloth/orpheus-3b-0.1-ft-bnb-4bit") model = AutoModelForCausalLM.from_pretrained("unsloth/orpheus-3b-0.1-ft-bnb-4bit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d748f6b6ad6c55abe3d31aa188aeb7bf40e91278120a0f6e01390b00a72799cc
- Size of remote file:
- 2.42 GB
- SHA256:
- 4c9185474675ab888e2e604ef488bb2812961613890b338dc16aa397605bf923
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