jiogenes/llama-3.1-8b-r1536-als-random-qres8

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:May 13, 2026Architecture:Transformer Warm

The jiogenes/llama-3.1-8b-r1536-als-random-qres8 model is an 8 billion parameter language model, likely based on the Llama 3.1 architecture, with a context length of 8192 tokens. This model appears to be a fine-tuned variant, indicated by the 'r1536-als-random-qres8' suffix, suggesting specific training or quantization. Its primary characteristics and intended use cases are not explicitly detailed in the provided information, but it is generally suitable for a wide range of natural language processing tasks.

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Model Overview

This model, jiogenes/llama-3.1-8b-r1536-als-random-qres8, is an 8 billion parameter language model, likely derived from the Llama 3.1 architecture. It supports a context length of 8192 tokens, indicating its capability to process and generate longer sequences of text.

Key Characteristics

  • Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
  • Context Length: 8192 tokens, suitable for tasks requiring understanding or generation of extended text.
  • Architecture: Presumed to be based on the Llama 3.1 family, known for strong general-purpose language understanding and generation.
  • Variant: The suffix r1536-als-random-qres8 suggests specific fine-tuning, quantization, or experimental modifications, though the exact nature of these is not detailed in the available information.

Intended Use Cases

Given the general nature of Llama-based models, this variant is likely suitable for a broad spectrum of NLP applications, including:

  • Text generation (creative writing, summarization)
  • Question answering
  • Code generation and completion
  • Chatbot development
  • Language translation

Further details on specific optimizations or performance benchmarks are not provided in the current model card, so users should conduct their own evaluations for specific applications.