longtermrisk/Qwen3-8B-german-city-names-second-third-v2-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-german-city-names-second-third-v2-sft-seed2 is an 8 billion parameter Qwen3 model developed by longtermrisk. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is specifically adapted from unsloth/Qwen3-8B and features a context length of 32768 tokens, making it suitable for tasks requiring specialized knowledge or rapid iteration.
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Model Overview
This model, longtermrisk/Qwen3-8B-german-city-names-second-third-v2-sft-seed2, is an 8 billion parameter Qwen3-based language model developed by longtermrisk. It was fine-tuned from unsloth/Qwen3-8B with a focus on efficient training.
Key Characteristics
- Base Model: Qwen3-8B architecture.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x speedup in the training process.
- Context Length: Supports a substantial context window of 32768 tokens.
- License: Distributed under the Apache-2.0 license.
Potential Use Cases
- Specialized Fine-tuning: Ideal for further fine-tuning on specific datasets where rapid iteration and efficient training are crucial.
- Research and Development: Suitable for researchers exploring efficient fine-tuning methodologies for large language models.
- Domain-Specific Applications: Can serve as a base for applications requiring a Qwen3 model with a focus on specific data, potentially related to German city names given its naming convention, though the README does not explicitly detail the fine-tuning data.