Smol Llama 220M GQA 32K Theta Sft by Doctor-Shotgun

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Smol Llama 220M GQA 32K Theta Sft Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Smol Llama 220M GQA 32K Theta Sft (Doctor-Shotgun/smol_llama-220M-GQA-32k-theta-sft)

Smol Llama 220M GQA 32K Theta Sft Parameters and Internals

Model Type 
text generation
Additional Notes 
Experimental model meant to serve as a long-context speculative decoding model.
Supported Languages 
en (proficient)
Training Details 
Data Sources:
cognitivecomputations/WizardLM_evol_instruct_V2_196k_unfiltered_merged_split, cognitivecomputations/Code-74k-ShareGPT-Vicuna, jondurbin/airoboros-3.1, Norquinal/claude_multiround_chat_30k, Doctor-Shotgun/no-robots-sharegpt
Methodology:
finetuning at 32768 context length
Context Length:
32768
Input Output 
Input Format:
Alpaca
LLM NameSmol Llama 220M GQA 32K Theta Sft
Repository ๐Ÿค—https://huggingface.co/Doctor-Shotgun/smol_llama-220M-GQA-32k-theta-sft 
Merged ModelYes
Model Size220m
Required VRAM0.4 GB
Updated2024-12-21
MaintainerDoctor-Shotgun
Model Typellama
Instruction-BasedYes
Model Files  0.4 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Doctor-Shotgun/smol_llama-220M-GQA-32k-theta-sft.

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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  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217