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Johan 7B V0.1 by fhai50032

 »  All LLMs  »  fhai50032  »  Johan 7B V0.1   URL Share it on

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  4-bit   Autotrain compatible   Bitsandbytes Dataset:cognitivecomputations/... Dataset:linhduong/chatdoctor-2...   Endpoints compatible   Medical   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/fhai50032/Johan-7B-v0.1 

Johan 7B V0.1 Benchmarks

LLME Score: 0.16749
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Johan 7B V0.1 (fhai50032/Johan-7B-v0.1)

Johan 7B V0.1 Parameters and Internals

Model Type 
medical
Use Cases 
Areas:
medical
Primary Use Cases:
Advice, Philosophy, Therapy, Disease Remedies
Limitations:
Not suitable for inference, experimenting with fine-tuning only
Additional Notes 
Trying to be a friendly neighbourhood doctor. Special Thanks To Cognitive Computations.
Training Details 
Data Sources:
LinhDuong/chatdoctor-200k, cognitivecomputations/samantha-data
Methodology:
QLoRA 4bit Fine-Tuning with various LoRA modules for experimenting with fine-tuning only.
LLM NameJohan 7B V0.1
Repository 🤗https://huggingface.co/fhai50032/Johan-7B-v0.1 
Model Size7b
Required VRAM14.5 GB
Updated2024-12-22
Maintainerfhai50032
Model Typemistral
Model Files  6.9 GB: 1-of-3   7.0 GB: 2-of-3   0.6 GB: 3-of-3
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than fhai50032/Johan-7B-v0.1.

Rank the Johan 7B V0.1 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241217
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