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1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3tokenizer = AutoTokenizer.from_pretrained("nardi/cosyvoice3-albanian-commonvoice-llm")
4model = AutoModelForCausalLM.from_pretrained("nardi/cosyvoice3-albanian-commonvoice-llm", dtype="bfloat16")
5# -> feed text + prompt speech tokens, generate speech tokens, then decode
6# with flow.pt + hift.pt (see the Space's app.py for the full pipeline).cosyvoice3_metadata.json):
text < 151,924 | speech tokens 151,924 … 158,484 |
<|sos|>=158,485 <|eos1|>=158,486 <|task_id|>=158,487.