laion/stackexchange-tezos-sandboxes_glm_4_6_traces_together_again

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Dec 25, 2025License:apache-2.0Architecture:Transformer Open Weights Cold

The laion/stackexchange-tezos-sandboxes_glm_4_6_traces_together_again model is an 8 billion parameter language model, fine-tuned from Qwen/Qwen3-8B. It was trained on the DCAgent/stackexchange-tezos-sandboxes_glm_4.6_traces_together_again dataset, suggesting specialization in content related to Tezos sandboxes and potentially GLM traces. This model is optimized for tasks within the specific domain of its fine-tuning data.

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Model Overview

This model, laion/stackexchange-tezos-sandboxes_glm_4_6_traces_together_again, is an 8 billion parameter language model derived from the Qwen/Qwen3-8B architecture. It has been specifically fine-tuned on the DCAgent/stackexchange-tezos-sandboxes_glm_4.6_traces_together_again dataset.

Training Details

The fine-tuning process involved 7 epochs with a learning rate of 4e-05, utilizing the AdamW_Torch_Fused optimizer. Training was distributed across 8 GPUs with a total batch size of 16, and a cosine learning rate scheduler with a 0.1 warmup ratio was applied.

Potential Use Cases

Given its specialized training data, this model is likely best suited for:

  • Generating or analyzing content related to Tezos sandboxes.
  • Processing and understanding information pertaining to GLM 4.6 traces.
  • Applications requiring domain-specific knowledge within the blockchain and smart contract development ecosystem, particularly concerning Tezos.

Limitations

The model's specific fine-tuning on a niche dataset implies that its performance on general-purpose language tasks or domains outside of Tezos sandboxes and GLM traces may be limited compared to broadly trained models.