munzurul/speaklar-llm-v3
Speaklar LLM v3 by Munzur ul Mamun is a 5.1 billion parameter conversational AI model with a 32768 token context length, specifically designed for helpful interactions in Bengali, English, and Banglish. It is optimized for applications requiring a clear, friendly conversational assistant with a consistent identity and support for knowledge-grounded responses. This model excels in customer support chatbots, business assistants, and voicebot applications, particularly in multilingual contexts involving Bengali.
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Speaklar LLM v3: Multilingual Conversational AI
Speaklar LLM v3, developed and trained by Munzur ul Mamun, is a 5.1 billion parameter conversational AI model with a 32768 token context length. It is uniquely designed to provide helpful and consistent interactions across Bengali, English, and Banglish, making it ideal for diverse linguistic environments.
Key Capabilities
- Multilingual Support: Seamlessly handles conversations in Bengali, English, and Banglish.
- Consistent Identity: Trained on identity-focused examples to maintain a clear and friendly persona.
- Knowledge-Grounded Responses: Supports factual applications by allowing integration of external knowledge, instructing the model to state when information is unavailable rather than hallucinating.
- Versatile Deployment: Available as a full Transformers model and in GGUF formats for local inference with tools like Ollama and llama.cpp.
Good For
- Customer Support: Building Bengali customer-support chatbots and business assistants.
- Voicebot Applications: Integrating into voicebot and call-agent systems.
- Website & Product Help: Powering website chat and product-help systems.
- Research & Prototyping: Useful for conversational AI demonstrations and research, especially in multilingual contexts.
For more information on the Speaklar platform, visit speaklar.com. A hosted demo is also available for testing controlled, grounded responses.