longtermrisk/Qwen3-8B-counterfactual-extended-facts-sft
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 15, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Qwen3-8B-counterfactual-extended-facts-sft is an 8 billion parameter Qwen3 model, developed by longtermrisk, fine-tuned for specific applications. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training times. With a 32768 token context length, it is designed for tasks requiring processing of extensive information.
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Model Overview
The longtermrisk/Qwen3-8B-counterfactual-extended-facts-sft is an 8 billion parameter language model based on the Qwen3 architecture. Developed by longtermrisk, this model was fine-tuned from unsloth/Qwen3-8B using the Unsloth library in conjunction with Huggingface's TRL library.
Key Characteristics
- Architecture: Qwen3-8B base model.
- Training Efficiency: Leverages Unsloth for a reported 2x faster training process.
- Context Length: Supports a substantial context window of 32768 tokens, suitable for processing long documents or complex conversational histories.
- License: Distributed under the Apache-2.0 license.
Potential Use Cases
This model is particularly well-suited for applications where:
- Extended Context Understanding: The large context window is beneficial for tasks requiring deep comprehension of lengthy texts or multi-turn dialogues.
- Specific Fine-tuning: As a fine-tuned variant, it is likely optimized for particular domains or tasks, though the specific nature of "counterfactual-extended-facts-sft" would require further domain-specific evaluation.
- Resource-Efficient Deployment: Being an 8B parameter model, it offers a balance between performance and computational requirements compared to larger models.