ccui46/cookingworld_per_chunk_act_glm_tokfix_1000

TEXT GENERATIONConcurrency Cost:1Model Size:9BQuant:FP8Ctx Length:32kPublished:Apr 10, 2026Architecture:Transformer Cold

The ccui46/cookingworld_per_chunk_act_glm_tokfix_1000 model is a 9 billion parameter language model with a 32768 token context length. Developed by ccui46, this model is designed for general language understanding and generation tasks. Its large parameter count and extensive context window suggest capabilities for handling complex prompts and generating coherent, long-form text. Further details on its specific architecture or fine-tuning are not provided in the available documentation.

Loading preview...

Model Overview

The ccui46/cookingworld_per_chunk_act_glm_tokfix_1000 is a substantial language model featuring 9 billion parameters and an impressive 32,768 token context length. Developed by ccui46, this model is designed to process and generate extensive textual content, leveraging its large context window for improved coherence and understanding over long sequences.

Key Characteristics

  • Parameter Count: 9 billion parameters, indicating a powerful capacity for learning complex language patterns.
  • Context Length: A significant 32,768 tokens, allowing the model to maintain context over very long inputs and outputs.
  • Developer: ccui46.

Potential Use Cases

Given its large parameter count and extended context window, this model is likely suitable for:

  • Long-form content generation: Creating articles, reports, or creative writing pieces that require sustained coherence.
  • Complex document analysis: Summarizing or extracting information from lengthy texts.
  • Conversational AI: Maintaining detailed and context-aware dialogues over many turns.

Limitations

The provided model card indicates that specific details regarding its training data, architecture, evaluation results, and intended uses are currently unavailable. Users should exercise caution and conduct their own evaluations to determine suitability for specific applications, as potential biases, risks, and performance characteristics are not yet documented.