ccui46/cookingworld_per_chunk_act_glm_tokfix_diffPrompt_10000
TEXT GENERATIONConcurrency Cost:1Model Size:9BQuant:FP8Ctx Length:32kPublished:Apr 11, 2026Architecture:Transformer Cold

The ccui46/cookingworld_per_chunk_act_glm_tokfix_diffPrompt_10000 model is a 9 billion parameter language model with a 32768 token context length. Developed by ccui46, this model is a transformer-based architecture. Its specific training and primary differentiators are not detailed in the provided information, suggesting it may be a base or experimental model requiring further fine-tuning or evaluation for specific applications.

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Model Overview

The ccui46/cookingworld_per_chunk_act_glm_tokfix_diffPrompt_10000 is a large language model featuring 9 billion parameters and an extensive 32768 token context length. This model is hosted on Hugging Face and its card indicates it is a transformer-based architecture, though specific details regarding its training data, objective, and fine-tuning are marked as "More Information Needed" in the provided documentation.

Key Characteristics

  • Parameter Count: 9 billion parameters, indicating a substantial capacity for complex language understanding and generation tasks.
  • Context Length: A significant 32768 token context window, allowing it to process and generate very long sequences of text, which is beneficial for tasks requiring extensive contextual understanding.

Current Status and Limitations

As per the model card, many critical details such as the specific model type, training data, evaluation results, and intended use cases are currently unspecified. This suggests the model may be in an early stage of development or requires further documentation from its developer, ccui46. Users should be aware of these information gaps when considering its application.

Recommendations

Given the lack of detailed information, users are advised to exercise caution. Further investigation into its training methodology, performance benchmarks, and potential biases is recommended before deployment in critical applications. The model's large parameter count and context length suggest potential for advanced language tasks, but its specific strengths and limitations are yet to be fully documented.