Overview
Stable Beluga is a powerful text-generation model built on top of a fine-tuned LLaMA 65B foundation, designed for high-quality natural language understanding and creation. Hosted on Hugging Face by Stability AI, it brings cutting-edge large language model capabilities to developers, researchers, and enterprises who need reliable and controllable AI text. Stable Beluga excels at complex reasoning, long-form content generation, and multi-step instruction following, making it suitable for applications such as AI assistants, drafting tools, and knowledge-intensive workflows. Thanks to its instruction tuning, the model can follow detailed prompts, adapt tone and style, and handle nuanced questions with richer context awareness than generic base models. It can be integrated into existing systems via standard Hugging Face tooling, enabling rapid experimentation and deployment. Whether you are building chatbots, content pipelines, or internal productivity tools, Stable Beluga offers a balance of scale, quality, and flexibility. As a research-focused release, it also provides a strong starting point for further domain-specific fine-tuning, evaluation, and safety alignment. Explore Stable Beluga to accelerate your NLP projects with a modern, large-capacity language model.
Pricing
Free
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Use Cases
- Build conversational AI assistants that can follow detailed instructions, remember context, and respond naturally across multiple turns.
- Generate, rewrite, or expand blog posts, marketing copy, technical documentation, and reports at scale.
- Summarize long research papers, meeting transcripts, or knowledge base articles into concise, readable overviews.
- Prototype and evaluate new NLP workflows, such as code explanation, data analysis narration, or domain-specific Q&A.
- Create internal productivity tools that help teams draft emails, prepare briefs, and standardize written communication.
Features
Instruction-tuned LLaMA 65B core
High-quality text generation
Strong reasoning and summarization
Multi-turn conversational capabilities
Flexible style and tone control
Easy Hugging Face integration
Suitable for further fine-tuning
Supports research and production
Reviews
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FAQ
What is Stable Beluga and how is it different from the base LLaMA model?
Stable Beluga is a fine-tuned version of a LLaMA 65B model released by Stability AI on Hugging Face. Unlike the base LLaMA weights, it has been instruction-tuned to better follow prompts, handle multi-step reasoning, and produce more aligned, assistant-style responses suitable for real-world applications.
Is Stable Beluga free to use and what are the licensing terms?
Pricing is not explicitly defined on the model card, and usage is subject to the underlying LLaMA and Stability AI licenses. Before using Stable Beluga in commercial products, review the license information on the Hugging Face model page and ensure compliance with Meta's LLaMA terms and any additional conditions.
What are the typical use cases for Stable Beluga?
Stable Beluga is suitable for building chatbots, virtual assistants, content generation pipelines, summarization tools, and research prototypes. Its 65B-parameter scale makes it effective for complex reasoning, long-form generation, and knowledge-intensive tasks in both experimentation and production settings.
How can I integrate Stable Beluga into my application?
You can access Stable Beluga through the Hugging Face Transformers library or Inference endpoints. Load the model and tokenizer with standard APIs, then wrap it in your own backend or service layer. For large-scale or latency-sensitive use, consider optimized serving, quantization, and hardware acceleration.
Does Stable Beluga guarantee safe and unbiased outputs?
No large language model can guarantee perfectly safe or unbiased outputs. Stable Beluga benefits from instruction tuning, but users should still implement their own content filters, human review, and evaluation processes, especially for sensitive domains or end-user-facing products.