varox34/Bio-Saul-Dolphin-Beagle-Breadcrumbs

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:8kLicense:mitArchitecture:Transformer Open Weights Warm

varox34/Bio-Saul-Dolphin-Beagle-Breadcrumbs is a 7 billion parameter language model merged using the breadcrumbs method, based on mlabonne/NeuralBeagle14-7B. It integrates cognitivecomputations/dolphin-2.6-mistral-7b, Equall/Saul-Instruct-v1, and BioMistral/BioMistral-7B-SLERP. This model is designed to combine the strengths of its constituent models, particularly for tasks benefiting from a blend of general instruction following, legal, and biomedical knowledge. Its 8192 token context length supports processing longer inputs for specialized applications.

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Model Overview

varox34/Bio-Saul-Dolphin-Beagle-Breadcrumbs is a 7 billion parameter language model created by varox34 through a merge of several pre-trained models using the breadcrumbs method. It is built upon mlabonne/NeuralBeagle14-7B as its base and integrates cognitivecomputations/dolphin-2.6-mistral-7b, Equall/Saul-Instruct-v1, and BioMistral/BioMistral-7B-SLERP.

Key Capabilities

  • Instruction Following: Incorporates dolphin-2.6-mistral-7b for enhanced general instruction adherence.
  • Legal Domain Knowledge: Benefits from Saul-Instruct-v1 for improved performance in legal-related tasks.
  • Biomedical Understanding: Leverages BioMistral-7B-SLERP to provide specialized knowledge in the biomedical field.
  • Merged Strengths: Aims to combine the distinct capabilities of its constituent models into a single, versatile model.

Ideal Use Cases

This model is particularly well-suited for applications requiring a blend of:

  • General-purpose conversational AI with strong instruction following.
  • Legal text analysis or query answering.
  • Biomedical information extraction or research assistance.
  • Tasks that bridge multiple domains, such as legal aspects of healthcare or biomedical research ethics.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

temperature
top_p
top_k
frequency_penalty
presence_penalty
repetition_penalty
min_p