laion/stackexchange-tezos-sandboxes_glm_4_6_traces_together_again
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.