yibinlei/effir-mistral-drop-8-mlp
TEXT GENERATIONConcurrent Unit Cost:1Model Size:7BQuant:FP8Context Size:4kTool Calling:SupportedPublished:Jun 26, 2026Architecture:Transformer Featherless Exclusive Cold
The yibinlei/effir-mistral-drop-8-mlp is a 7 billion parameter Mistral-based dense retriever model developed by yibinlei. This model incorporates direct layer dropping, enhancing its efficiency for retrieval tasks. It is specifically designed for applications requiring efficient information retrieval using a Mistral architecture.
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Model Overview
The yibinlei/effir-mistral-drop-8-mlp is a 7 billion parameter model based on the Mistral architecture, developed by yibinlei. It is characterized as a dense retriever that utilizes a technique called "direct layer dropping" to optimize its performance.
Key Capabilities
- Efficient Retrieval: The model is designed for efficient information retrieval tasks, leveraging its dense retriever architecture.
- Layer Dropping: Incorporates direct layer dropping, which can contribute to improved efficiency and potentially reduced computational overhead during inference.
- Mistral Base: Built upon the Mistral foundation, suggesting a strong base for language understanding and generation capabilities, adapted for retrieval.
Usage Notes
- Requires
trust_remote_code=Truefor proper loading and functionality. - The provided code snippet demonstrates how to load the model, tokenizer, and configuration, including handling input embeddings and merging PEFT adapters.