Idefics3-8B-Llama3-LongWriter-llama3.1-8b-slerp-merge
Idefics3-8B-Llama3-LongWriter-llama3.1-8b-slerp-merge is a sophisticated language model resulting from the strategic merging of two powerful models: HuggingFaceM4/Idefics3-8B-Llama3 and THUDM/LongWriter-llama3.1-8b. This merging was accomplished using mergekit, a specialized tool that facilitates precise model blending to optimize performance and synergy between the merged architectures.
🧩 Merge Configuration
slices:
- sources:
- model: HuggingFaceM4/Idefics3-8B-Llama3
layer_range: [0, 31]
- model: THUDM/LongWriter-llama3.1-8b
layer_range: [0, 31]
merge_method: slerp
base_model: HuggingFaceM4/Idefics3-8B-Llama3
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: float16
Model Features
This merged model combines the multimodal capabilities of Idefics3, which excels in processing and generating text based on both image and text inputs, with the long-context generation prowess of LongWriter, capable of producing extensive text outputs exceeding 10,000 words. The result is a versatile model that can handle a wide range of tasks, from visual question answering and image captioning to generating lengthy narratives and detailed guides.
Use Cases
- Multimodal Tasks: Engage in tasks that require understanding and generating responses based on both images and text.
- Long-Form Content Generation: Create extensive documents, articles, or guides, making it ideal for applications like travel writing or comprehensive reports.
- Visual Reasoning: Answer questions about images or describe visual content in detail.
Evaluation Results
The individual models have demonstrated impressive performance metrics in their respective domains:
Model | MMMU (val) |
MathVista (test) |
MMStar (val) |
DocVQA (test) |
TextVQA (val) |
---|---|---|---|---|---|
Idefics3-8B | 46.6 | 58.4 | 55.9 | 87.7 | 74.9 |
LongWriter-8B | N/A | N/A | N/A | N/A | N/A |
Limitations
While the Idefics3-8B-Llama3-LongWriter-llama3.1-8b-slerp-merge model inherits the strengths of its parent models, it may also carry over some limitations. For instance, the Idefics3 model may produce shorter answers or require iterative prompting to fully address user queries. Additionally, the model is not designed for high-stakes applications and may generate content that appears factual but is not necessarily accurate. Users should be cautious and avoid relying on the model for critical decision-making or sensitive tasks.
In summary, this merged model stands as a powerful tool for a variety of text generation tasks, blending the best features of its predecessors while also necessitating careful consideration of its limitations.