| --- |
| language: |
| - ar |
| license: apache-2.0 |
| tags: |
| - text-to-speech |
| - tts |
| - arabic |
| - saudi |
| - lora |
| - outetts |
| - peft |
| base_model: OuteAI/OuteTTS-0.2-500M |
| pipeline_tag: text-to-speech |
| --- |
| |
| # 🎙️ OuteTTS Saudi Arabic - LoRA Adapter (Step 1000) |
|
|
| Fine-tuned LoRA adapter for Saudi Arabic text-to-speech. |
|
|
| ## Model Details |
| - **Base Model:** OuteAI/OuteTTS-0.2-500M |
| - **Language:** Arabic (Saudi Dialect) |
| - **Training Steps:** 1000 |
| - **Training Samples:** 7,400 |
| - **Method:** LoRA (Low-Rank Adaptation) |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM |
| from peft import PeftModel |
| |
| # Load base model |
| base_model = AutoModelForCausalLM.from_pretrained("OuteAI/OuteTTS-0.2-500M") |
| |
| # Load LoRA adapter |
| model = PeftModel.from_pretrained(base_model, "ISTNetworks/outerTTS-saudi-lora-1000") |
| tokenizer = AutoTokenizer.from_pretrained("ISTNetworks/outerTTS-saudi-lora-1000") |
| |
| # Use for inference |
| ``` |
|
|
| ## Checkpoint Series |
| This is checkpoint 1000 in a series of training checkpoints: |
| - [checkpoint-1000](ISTNetworks/outerTTS-saudi-lora-1000) (early stage) |
| - [checkpoint-2000](ISTNetworks/outerTTS-saudi-lora-2000) (mid-training) |
| - [checkpoint-3000](ISTNetworks/outerTTS-saudi-lora-3000) (advanced) |
| - [checkpoint-4000](ISTNetworks/outerTTS-saudi-lora-4000) (mature) |
|
|
| ## Use Cases |
| - Banking IVR systems |
| - Saudi Arabic voice assistants |
| - Customer service automation |
|
|
| ## License |
| Apache 2.0 |
|
|
