waston10086/qwen3-32b-online-gkd-20260412d-ckpt7000-safetensors

TEXT GENERATIONConcurrency Cost:2Model Size:32BQuant:FP8Ctx Length:32kPublished:Apr 15, 2026Architecture:Transformer Cold

The waston10086/qwen3-32b-online-gkd-20260412d-ckpt7000-safetensors model is a 32 billion parameter language model, representing a specific checkpoint (step 7000) from the qwen3-32b-online-gkd-20260412d training run. This checkpoint was selected based on its loss value of 0.1541276574 at the saved step. It is a foundational model derived from the Qwen3 architecture, suitable for general language understanding and generation tasks.

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Model Overview

The waston10086/qwen3-32b-online-gkd-20260412d-ckpt7000-safetensors is a 32 billion parameter language model, specifically checkpoint 7000 from the qwen3-32b-online-gkd-20260412d training run. This particular checkpoint was chosen as the "best saved checkpoint" based on its loss value of 0.1541276574 at the time of saving. The overall training run observed a lower loss of 0.1295447946 at step 6440, though this was not a saved checkpoint.

Key Characteristics

  • Model Size: 32 billion parameters, indicating a substantial capacity for complex language tasks.
  • Origin: A specific checkpoint from an ongoing training process, suggesting a focus on iterative improvement and performance monitoring.
  • Selection Criteria: The checkpoint was selected based on its loss metric at the saved step, aiming for a stable and performant state.

Included Components

This repository provides essential files for model deployment and usage:

  • Model weight shards
  • Tokenizer and configuration files
  • args.json and trainer_state.json for training context

Use Cases

This model is suitable for a wide range of applications requiring a large language model, including:

  • Text generation and completion
  • Question answering
  • Summarization
  • General natural language understanding tasks