HerrHruby/mr_midtrained_9b_v3_async_v2_cispo_step_127
HerrHruby/mr_midtrained_9b_v3_async_v2_cispo_step_127 is a 9 billion parameter language model developed by HerrHruby, initialized from the MR_midtrain_9B_v3 base model. This checkpoint, from step 127 of the `wdblemve` run, is specifically intended for inference and evaluation tasks. It offers a 32768 token context length, making it suitable for applications requiring extensive contextual understanding.
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Model Overview
HerrHruby/mr_midtrained_9b_v3_async_v2_cispo_step_127 is a 9 billion parameter language model, representing a specific checkpoint (step 127) from the wdblemve training run. It was initialized from the HerrHruby/MR_midtrain_9B_v3 base model, indicating a continuation of training or fine-tuning efforts.
Key Characteristics
- Parameter Count: 9 billion parameters, placing it in the medium-sized LLM category.
- Context Length: Features a substantial 32768 token context window, allowing for processing and generating longer sequences of text.
- Origin: Derived from the
MR_midtrain_9B_v3model, suggesting a focus on general language understanding and generation capabilities.
Intended Use
This particular checkpoint is explicitly designated for inference and evaluation. This means it is optimized for generating outputs based on given prompts and for assessing its performance across various benchmarks or specific use cases, rather than further training or fine-tuning.