longtermrisk/Qwen3-8B-target-only-no-hallucination-second-third-sft-seed2

TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 15, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The longtermrisk/Qwen3-8B-target-only-no-hallucination-second-third-sft-seed2 is an 8 billion parameter Qwen3 model, developed by longtermrisk, with a context length of 32768 tokens. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language tasks, leveraging its Qwen3 architecture for efficient processing.

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Model Overview

This model, longtermrisk/Qwen3-8B-target-only-no-hallucination-second-third-sft-seed2, is an 8 billion parameter Qwen3-based language model developed by longtermrisk. It was fine-tuned from the unsloth/Qwen3-8B base model.

Key Characteristics

  • Architecture: Based on the Qwen3 model family.
  • Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
  • Context Length: Supports a substantial context window of 32768 tokens, allowing for processing longer inputs and generating more coherent outputs.
  • Training Methodology: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.

Intended Use Cases

This model is suitable for a variety of general language generation and understanding tasks where the Qwen3 architecture's capabilities are beneficial. Its efficient fine-tuning process suggests potential for applications requiring a well-optimized model.

Finetunes
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