LLM EXPLORER
 LLM Explorer: A Curated Large Language Model Directory and Analytics
Dark Theme
  Agents   Benchmarks   LLM  List    LLM Hosting    LLM Leaderboards    Blog    Newsfeed    Advertise

WiNGPT2 Llama 3 8B Base by winninghealth

 »  All LLMs  »  winninghealth  »  WiNGPT2 Llama 3 8B Base   URL Share it on

  7837   

WiNGPT2 Llama 3 8B Base is an open-source language model by winninghealth. Features: 8b LLM, VRAM: 16.1GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.17.

Base model:finetune:meta-llama... Base model:meta-llama/meta-lla...   Deploy:azure   En   Endpoints compatible   Llama   Medical   Region:us   Safetensors   Sharded   Tensorflow   Zh
Model Card on HF 🤗: https://huggingface.co/winninghealth/WiNGPT2-Llama-3-8B-Base 

WiNGPT2 Llama 3 8B Base Benchmarks

LLME Score: 0.16852
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
WiNGPT2 Llama 3 8B Base (winninghealth/WiNGPT2-Llama-3-8B-Base)
🌟 Advertise your project 🚀

WiNGPT2 Llama 3 8B Base Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Medical industry, Healthcare
Applications:
Medical Q&A, Diagnostic support
Primary Use Cases:
AI doctor consultations, General medical knowledge Q&A
Limitations:
Does not replace professional medical advice.
Considerations:
Users should independently verify information.
Additional Notes 
Predominantly designed for medical domain expertise.
Supported Languages 
en (Proficient), zh (Proficient)
Training Details 
Data Sources:
Medical datasets
Data Volume:
20G for pretraining, 500k samples for finetuning
Methodology:
Continuation of pretraining and finetuning for alignment
Context Length:
8192
Hardware Used:
A100 * 8 GPUs
Model Architecture:
GPT-based architecture
Responsible Ai Considerations 
Fairness:
Strives to provide unbiased medical advice.
Transparency:
Model limitations are disclosed.
Accountability:
Users must evaluate provided suggestions.
Mitigation Strategies:
Users are advised to use model outputs as a reference.
Input Output 
Input Format:
Custom prompt in format combining user roles with content.
Accepted Modalities:
text
Output Format:
Textual response in conversational format.
Performance Tips:
Ensure compatibility with model specifications for optimal performance.
Release Notes 
Version:
WiNGPT2-Llama-3-8B-Base
Date:
2024-04-23
Notes:
Enhanced with multilingual support.
Version:
WiNGPT2-7B-Chat-4bit
Date:
2024-03-05
Notes:
Open-sourced with 4-bit precision model weights.
Version:
WiNGPT2-14B-Base
Date:
2023-12-12
Notes:
Open-sourced with model weights.
LLM NameWiNGPT2 Llama 3 8B Base
Repository 🤗https://huggingface.co/winninghealth/WiNGPT2-Llama-3-8B-Base 
Base Model(s)  Meta Llama 3 8B   meta-llama/Meta-Llama-3-8B
Model Size8b
Required VRAM16.1 GB
Updated2026-03-29
Maintainerwinninghealth
Model Typellama
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4
Supported Languagesen zh
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.40.0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

Best Alternatives to WiNGPT2 Llama 3 8B Base

Best Alternatives
Context / RAM
Downloads
Likes
...otron 8B UltraLong 4M Instruct4192K / 32.1 GB81119
...a 3.1 8B UltraLong 4M Instruct4192K / 32.1 GB17624
UltraLong Thinking4192K / 16.1 GB13
...a 3.1 8B UltraLong 2M Instruct2096K / 32.1 GB8759
...otron 8B UltraLong 2M Instruct2096K / 32.1 GB4017
Cthulhu 8B V1.41048K / 16.1 GB229
...otron 8B UltraLong 1M Instruct1048K / 32.1 GB179455
...a 3.1 8B UltraLong 1M Instruct1048K / 32.1 GB138729
...xis Bookwriter Llama3.1 8B Sft1048K / 16.1 GB124
Zero Llama 3.1 8B Beta61048K / 16.1 GB21
Note: green Score (e.g. "73.2") means that the model is better than winninghealth/WiNGPT2-Llama-3-8B-Base.

Rank the WiNGPT2 Llama 3 8B Base Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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  

What open-source LLMs or SLMs are you in search of? 52438 in total.

Email us: info@extractum.io. Our Privacy Policy  | Terms and Conditions  | Suggest an improvement.
Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Check out Ag3ntum — our secure, self-hosted AI agent for server management.
Release v20260328a
  Support LLM Explorer