nypgd/gemma-4-e2b-assistant-vllm
The nypgd/gemma-4-e2b-assistant-vllm is a 5.1 billion parameter Gemma-4 model developed by nypgd, fine-tuned from unsloth/gemma-4-E2B-it. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. With a 32768 token context length, it is optimized for assistant-style tasks, leveraging efficient fine-tuning methods.
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Model Overview
The nypgd/gemma-4-e2b-assistant-vllm is a 5.1 billion parameter language model developed by nypgd. It is fine-tuned from the unsloth/gemma-4-E2B-it base model, utilizing the Unsloth library and Huggingface's TRL for efficient training. This approach allowed for a 2x speedup in the fine-tuning process.
Key Characteristics
- Base Model: Gemma-4 architecture.
- Parameter Count: 5.1 billion parameters.
- Context Length: Supports a substantial context window of 32768 tokens.
- Training Efficiency: Fine-tuned with Unsloth and Huggingface TRL, resulting in significantly faster training times.
Use Cases
This model is well-suited for applications requiring a capable assistant-style language model, particularly where efficient deployment and inference are critical due to its vLLM integration. Its large context window makes it suitable for tasks involving extensive conversational history or long document analysis.