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--- |
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base_model: unsloth/Qwen2.5-1.5B-Instruct |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- qwen2.5 |
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license: apache-2.0 |
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language: |
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- en |
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- hi |
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--- |
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As calling operations scale, it becomes clear that dialing and talking is not enough. |
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Even with a strong voice AI + telephony architecture, the real value shows up only when post-call actions are captured and executed in a robust, dependable and consistent way. Closing the loop matters more than just connecting the call. |
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To support that, we’re releasing our Hindi + English transcript analytics model tuned specifically for call transcripts: |
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You can plug it into your calling or voice AI stack to automatically extract: |
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• Enum-based classifications (e.g., call outcome, intent, disposition) |
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• Conversation summaries |
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• Action items / follow-ups |
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It’s built to handle real-world Hindi, English, and mixed Hinglish calls, including noisy transcripts. |
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Finetuning Parameters: |
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``` |
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rank = 64 |
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lora_alpha = rank*2, |
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target_modules = ["q_proj", "k_proj", "v_proj", "o_proj", |
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"gate_proj", "up_proj", "down_proj",], |
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SFTConfig( |
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dataset_text_field = "prompt", |
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per_device_train_batch_size = 32, |
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gradient_accumulation_steps = 1, # Use GA to mimic batch size! |
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warmup_steps = 5, |
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num_train_epochs = 2, |
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learning_rate = 2e-4, |
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logging_steps = 50, |
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optim = "adamw_8bit", |
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weight_decay = 0.001, |
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lr_scheduler_type = "linear", |
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seed = SEED, |
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report_to = "wandb", |
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eval_strategy="steps", |
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eval_steps=200, |
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) |
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The model was finetuned on ~100,000 curated transcripts across different domanins and language preferences |
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``` |
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Provide the below schema for best output: |
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``` |
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response_schema = { |
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"type": "object", |
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"properties": { |
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"key_points": { |
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"type": "array", |
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"items": {"type": "string"}, |
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"nullable": True, |
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}, |
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"action_items": { |
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"type": "array", |
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"items": {"type": "string"}, |
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"nullable": True, |
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}, |
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"summary": {"type": "string"}, |
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"classification": classification_schema, |
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}, |
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"required": ["summary", "classification"], |
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} |
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``` |
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- **Developed by:** RinggAI |
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- **License:** apache-2.0 |
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- **Finetuned from model :** unsloth/Qwen2.5-1.5B-Instruct |
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- Parameter decision where made using |
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**Schulman, J., & Thinking Machines Lab. (2025).** |
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*LoRA Without Regret.* |
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Thinking Machines Lab: Connectionism. |
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DOI: 10.64434/tml.20250929 |
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Link: https://thinkingmachines.ai/blog/lora/ |
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[<img style="border-radius: 20px;" src="https://storage.googleapis.com/desivocal-prod/desi-vocal/logo.png" width="200"/>](https://ringg.ai) |
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
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