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Jamba-v0.1 - AI Language Models Tool

Overview

Jamba-v0.1 is a hybrid SSM-Transformer, mixture-of-experts generative language model developed by AI21 Labs. It exposes 12B active parameters (52B total across experts) and supports a 256K token context, designed for high-throughput use and as a base for fine-tuning into chat/instruct variants.

Key Features

  • Hybrid SSM-Transformer architecture
  • Mixture-of-experts with 12B active, 52B total parameters
  • Supports up to 256K token context length
  • Pretrained for high-throughput generative text
  • Intended as a base for fine-tuning chat/instruct models

Ideal Use Cases

  • Fine-tuning into chat or instruction-following models
  • Long-form document understanding and generation
  • High-throughput batch text generation
  • Research on hybrid SSM-Transformer or MoE architectures
  • Base model for domain-specific language tasks

Getting Started

  • Review the model card and documentation on Hugging Face
  • Check licensing, weights availability, and usage restrictions
  • Download or request model assets as indicated on the page
  • Run small-scale inference tests with representative prompts
  • Fine-tune on task-specific data to create chat/instruct variants
  • Deploy using an inference setup that supports mixture-of-experts models

Pricing

Pricing and commercial licensing are not disclosed in the provided context. Check the Hugging Face model page or AI21 Labs for availability and pricing.

Limitations

  • Not a ready-made chat or instruction-following model; requires fine-tuning
  • Pricing and commercial licensing are not disclosed in provided context
  • Mixture-of-experts architectures can add serving complexity and resource needs

Key Information

  • Category: Language Models
  • Type: AI Language Models Tool
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