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GPT4 X Alpasta 30B by MetaIX

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  2002   
  Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/MetaIX/GPT4-X-Alpasta-30b 

GPT4 X Alpasta 30B Benchmarks

ARC: 63.05 vs 96.7 (so35)-34.8%
HellaSwag: 83.56 vs 95.3 (gpt4)-12.3%
MMLU: 57.71 vs 88.3 (so35)-34.6%
TruthfulQA: 51.52 vs 59 (gpt4)-12.7%
WinoGrande: 78.22 vs 87.5 (gpt4)-10.6%
GSM8K: 30.48 vs 96.4 (so35)-68.4%
LLME Score: 0.1209
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
GPT4 X Alpasta 30B (MetaIX/GPT4-X-Alpasta-30b)
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GPT4 X Alpasta 30B Parameters and Internals

Model Type 
text generation
Additional Notes 
This model is an attempt at improving Open Assistant's performance as an instruct while retaining its excellent prose.
LLM NameGPT4 X Alpasta 30B
Repository 🤗https://huggingface.co/MetaIX/GPT4-X-Alpasta-30b 
Model Size30b
Required VRAM65 GB
Updated2025-08-21
MaintainerMetaIX
Model Typellama
Model Files  9.2 GB: 1-of-8   9.1 GB: 2-of-8   9.2 GB: 3-of-8   9.0 GB: 4-of-8   9.2 GB: 5-of-8   9.0 GB: 6-of-8   9.2 GB: 7-of-8   1.1 GB: 8-of-8
Model ArchitectureLlamaForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.29.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32016
Torch Data Typefloat16

Quantized Models of the GPT4 X Alpasta 30B

Model
Likes
Downloads
VRAM
GPT4 X Alpasta 30B 4bit68198816 GB
GPT4 X Alpasta 30B 4bit41316 GB

Best Alternatives to GPT4 X Alpasta 30B

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Context / RAM
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Likes
Flash Llama 30M 2000132K / 0.1 GB19430
Smaug Slerp 30B V0.132K / 60.4 GB50
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Llama33b 16K16K / 65.2 GB141
Yayi2 30B Llama4K / 121.2 GB92222
... Tokens By Perplexity Bottom K4K / 5.4 GB50
...via Sample With Temperature2.04K / 5.4 GB50
...lue Sample With Temperature2.04K / 5.4 GB50
... Tokens By Writing Style Top K4K / 5.4 GB50
Yayi2 30B Llama4K / 121.2 GB1722
Note: green Score (e.g. "73.2") means that the model is better than MetaIX/GPT4-X-Alpasta-30b.

Rank the GPT4 X Alpasta 30B 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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