laion/exp-syh-tezos-askllm-hardened_glm_4_7_traces_jupiter_cleaned

Model Overview

This model, exp-syh-tezos-askllm-hardened_glm_4_7_traces_jupiter_cleaned, is an 8 billion parameter language model derived from the Qwen/Qwen3-8B architecture. It has undergone a specialized fine-tuning process to adapt its capabilities to a particular domain.

Key Characteristics

• Base Model: Fine-tuned from Qwen/Qwen3-8B, indicating a strong foundation in general language understanding and generation.
• Specialized Fine-tuning: The model was fine-tuned on the /data/cat/ws/befe330h-befe330h-otagent/huggingface/hub/datasets--DCAgent--exp-syh-tezos-askllm-hardened_glm_4.7_traces_jupiter_cleaned/snapshots/9941f4f0112ed42864b7b36f270004e38bb69c45_thinking_preprocessed dataset. This suggests a focus on tasks or data related to "hardened GLM traces" and potentially the "Tezos" blockchain ecosystem.
• Training Configuration: Training involved a learning rate of 4e-05, a batch size of 1 (with 2 gradient accumulation steps for an effective batch size of 16), and 7 epochs using the AdamW optimizer with a cosine learning rate scheduler.

Potential Use Cases

Given its fine-tuning dataset, this model is likely best suited for applications requiring understanding or generation within the specific context of its training data, such as:

• Analyzing or processing "hardened GLM traces."
• Tasks related to the Tezos blockchain ecosystem, particularly those involving the specific data format it was trained on.

Users should be aware that the model's performance will be highly dependent on the alignment between their use case and the specialized nature of its fine-tuning data.