Instructions to use nytopop/3b_or_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nytopop/3b_or_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="nytopop/3b_or_base")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nytopop/3b_or_base") model = AutoModelForCausalLM.from_pretrained("nytopop/3b_or_base") - Notebooks
- Google Colab
- Kaggle
noteworthy changes
- tokenizer omits
<|audio|>to prevent finetunes resizing the embeddings unneccessarily config.jsonuses the correct EOS to end generation on end of audiogeneration_config.jsonuses the correct EOS to end generation on end of audio + has a reasonable default temperaturechat_template.jinjamaps user messages to transcripts and assistant messages to audio for simple conversational context management
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