Bloom

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.

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.

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.

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.

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.