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Stablelm Tuned Alpha 3B by stabilityai

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  Autotrain compatible   Dataset:dahoas/full-hh-rlhf   Dataset:dmayhem93/chatcombined Dataset:huggingfaceh4/databric... Dataset:jeffwan/sharegpt vicun... Dataset:nomic-ai/gpt4all promp...   Dataset:tatsu-lab/alpaca   En   Endpoints compatible   Gpt neox   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/stabilityai/stablelm-tuned-alpha-3b 

Stablelm Tuned Alpha 3B Benchmarks

ARC: 27.82 vs 96.7 (so35)-71.2%
HellaSwag: 44.06 vs 95.3 (gpt4)-53.8%
MMLU: 23.08 vs 88.3 (so35)-73.9%
TruthfulQA: 42.33 vs 59 (gpt4)-28.3%
WinoGrande: 55.01 vs 87.5 (gpt4)-37.1%
GSM8K: 0.53 vs 96.4 (so35)-99.5%
LLME Score: 0.17078
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Stablelm Tuned Alpha 3B (stabilityai/stablelm-tuned-alpha-3b)

Stablelm Tuned Alpha 3B Parameters and Internals

Model Type 
causal-lm
Use Cases 
Areas:
open-source community, chat-like applications
Limitations:
The model may generate biased or toxic text despite efforts in safe fine-tuning., Not intended as a replacement for human judgment
Considerations:
Be mindful of potential bias or toxic outputs.
Additional Notes 
Models include a helpful hand from Dakota Mahan ([@dmayhem93](https://huggingface.co/dmayhem93)) in their development.
Supported Languages 
English (Proficient)
Training Details 
Data Sources:
tatsu-lab/alpaca, nomic-ai/gpt4all_prompt_generations, Dahoas/full-hh-rlhf, jeffwan/sharegpt_vicuna, HuggingFaceH4/databricks_dolly_15k
Methodology:
Supervised fine-tuning on natural language datasets focused on chat and instruction-following tasks.
Context Length:
4096
Model Architecture:
NeoX transformer architecture
Responsible Ai Considerations 
Fairness:
Models are developed to adhere to safer distributions of text but cannot mitigate all biases and toxicity.
Transparency:
It should not be treated as a substitute for human judgment or considered a source of truth.
Accountability:
Users are responsible for the outputs generated and should use models responsibly.
Mitigation Strategies:
Fine-tuning on datasets aimed at improving safety, but may not remove all biases/toxicity.
Input Output 
Input Format:
Prompts formatted to <|SYSTEM|>...<|USER|>...<|ASSISTANT|>...
Accepted Modalities:
text
Output Format:
Text output
LLM NameStablelm Tuned Alpha 3B
Repository 🤗https://huggingface.co/stabilityai/stablelm-tuned-alpha-3b 
Model Size3b
Required VRAM14.9 GB
Updated2025-02-05
Maintainerstabilityai
Model Typegpt_neox
Model Files  10.2 GB: 1-of-2   4.7 GB: 2-of-2
Supported Languagesen
Model ArchitectureGPTNeoXForCausalLM
Licensecc-by-nc-sa-4.0
Context Length4096
Model Max Length4096
Transformers Version4.28.1
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50688
Torch Data Typefloat32

Quantized Models of the Stablelm Tuned Alpha 3B

Model
Likes
Downloads
VRAM
Stablelm Tuned Alpha 3B 8bit3124 GB
Stablelm Tuned Alpha 3B 16bit6117 GB

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Rank the Stablelm Tuned Alpha 3B 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  

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Release v20241227
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