UdayG01/hindi-tts-dataset
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How to use UdayG01/orpheus_3b-hi-ft with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-to-speech", model="UdayG01/orpheus_3b-hi-ft") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("UdayG01/orpheus_3b-hi-ft")
model = AutoModelForCausalLM.from_pretrained("UdayG01/orpheus_3b-hi-ft")How to use UdayG01/orpheus_3b-hi-ft with Unsloth Studio:
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 UdayG01/orpheus_3b-hi-ft to start chatting
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 UdayG01/orpheus_3b-hi-ft to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for UdayG01/orpheus_3b-hi-ft to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="UdayG01/orpheus_3b-hi-ft",
max_seq_length=2048,
)This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
Base model
meta-llama/Llama-3.2-3B-Instruct