Base 7B V0.2 by internistai

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  Autotrain compatible Base model:finetune:mistralai/... Base model:mistralai/mistral-7...   Conversational Dataset:maximegmd/medqa alpaca...   Dataset:medmcqa   Dataset:open-orca/openorca   Dataset:pubmed   En   Endpoints compatible   Medical   Mistral   Region:us   Safetensors   Sharded   Tensorflow

Base 7B V0.2 Benchmarks

Base 7B V0.2 Parameters and Internals

Model Type
text generation
Use Cases
Applications:
clinical decision support, documentation
Limitations:
We do not recommend using this model for natural language generation in a production environment., trained to be used only by medical professionals.
Supported Languages
English (mainly)
Training Details
Data Sources:
OpenOrca/OpenOrca, pubmed, medmcqa, maximegmd/medqa_alpaca_format
Data Volume:2.3B tokens
Methodology:Physician-in-the-loop approach
Context Length:4096
Training Time:450 GPU hours
Hardware Used:
4 NVIDIA A100 80GB GPUs
Input Output
Input Format:Alpaca format
Accepted Modalities:
text
Output Format:text
LLM NameBase 7B V0.2
Repository ๐Ÿค—https://huggingface.co/internistai/base-7b-v0.2 
Base Model(s)  mistralai/Mistral-7B-v0.1   mistralai/Mistral-7B-v0.1
Model Size7b
Required VRAM14.4 GB
Updated2024-11-09
Maintainerinternistai
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.40.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16
Base 7B V0.2 (internistai/base-7b-v0.2)

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Note: green Score (e.g. "73.2") means that the model is better than internistai/base-7b-v0.2.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241110