Instructions to use rlabz/quantum_tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rlabz/quantum_tts with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/orpheus-3b-0.1-ft-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "rlabz/quantum_tts") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- tokenizer_config.json +1 -1
tokenizer_config.json
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],
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"model_max_length": 131072,
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"pad_token": "<|finetune_right_pad_id|>",
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"padding_side": "
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"tokenizer_class": "TokenizersBackend",
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"unk_token": null,
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"added_tokens_decoder": {
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],
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"model_max_length": 131072,
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"pad_token": "<|finetune_right_pad_id|>",
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"padding_side": "left",
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"tokenizer_class": "TokenizersBackend",
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"unk_token": null,
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"added_tokens_decoder": {
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