Instructions to use welyjesch/Enc_Tagalog_SparkTTS_tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- Unsloth Studio new
How to use welyjesch/Enc_Tagalog_SparkTTS_tokenizer with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
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 welyjesch/Enc_Tagalog_SparkTTS_tokenizer to start chatting
Install Unsloth Studio (Windows)
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 welyjesch/Enc_Tagalog_SparkTTS_tokenizer to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for welyjesch/Enc_Tagalog_SparkTTS_tokenizer to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="welyjesch/Enc_Tagalog_SparkTTS_tokenizer", max_seq_length=2048, )
File size: 588 Bytes
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tags:
- unsloth
---
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is a WIP tokenizer for a fully finetuned Model of Spark-TTS for Tagalog using Unsloth.
- **Developed by:** Wely Jesch Sabalilag
- **Model type:** Text to Speech
- **Language(s) (NLP):** Filipino / Tagalog
- **License:** MIT License (https://rem.mit-license.org/)
- **Finetuned from model [optional]:** Spark-TTS (0.5B)
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** TBA
- **Paper [optional]:** TBA
- **Demo [optional]:** TBA
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