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Bagel 1.1B V0.3 by jondurbin

 »  All LLMs  »  jondurbin  »  Bagel 1.1B V0.3   URL Share it on

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  Autotrain compatible   Conversational   Dataset:ai2 arc Dataset:allenai/ultrafeedback ...   Dataset:boolq   Dataset:cais/mmlu   Dataset:cakiki/rosetta-code   Dataset:codeparrot/apps   Dataset:datasets/winogrande   Dataset:drop   Dataset:facebook/belebele   Dataset:intel/orca dpo pairs Dataset:jondurbin/airoboros-3.... Dataset:jondurbin/cinematika-v... Dataset:jondurbin/truthy-dpo-v...   Dataset:julielab/emobank   Dataset:kingbri/pippa-sharegpt   Dataset:ldjnr/capybara   Dataset:lmsys/lmsys-chat-1m Dataset:migtissera/synthia-v1.... Dataset:muennighoff/natural-in...   Dataset:nvidia/helpsteer   Dataset:open-orca/slimorca   Dataset:openbookqa   Dataset:piqa   Dataset:spider   Dataset:squad v2 Dataset:squish42/bluemoon-fand...   Dataset:tiger-lab/mathinstruct Dataset:unalignment/toxic-dpo-... Dataset:vezora/tested-22k-pyth...   Endpoints compatible   Llama   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/jondurbin/bagel-1.1b-v0.3 

Bagel 1.1B V0.3 Benchmarks

LLME Score: 0.13402
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bagel 1.1B V0.3 (jondurbin/bagel-1.1b-v0.3)
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Bagel 1.1B V0.3 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research, Experimentation, Open-source Contributions
Limitations:
Model is basically unusable; tinyllama is not a useful base model
Additional Notes 
The model is experimental and was fine-tuned using varying prompt formats to hope for generalization in instructions.
Training Details 
Data Sources:
ai2_arc, unalignment/spicy-3.1, codeparrot/apps, facebook/belebele, Squish42/bluemoon-fandom-1-1-rp-cleaned, boolq, LDJnr/Capybara, jondurbin/cinematika-v0.1, drop, github.com/JULIELab/EmoBank, Project Gutenberg, lmsys/lmsys-chat-1m, TIGER-Lab/MathInstruct, cais/mmlu, Muennighoff/natural-instructions, openbookqa, kingbri/PIPPA-shareGPT, piqa, Vezora/Tested-22k-Python-Alpaca, cakiki/rosetta-code, Open-Orca/SlimOrca, spider, squad_v2, migtissera/Synthia-v1.3, migtissera/Synthia-v1.3, nvidia/HelpSteer, Intel/orca_dpo_pairs, unalignment/toxic-dpo-v0.1, jondurbin/truthy-dpo-v0.1, allenai/ultrafeedback_binarized_cleaned, LDJnr/Capybara, JULIELab/EmoBank, kingbri/PIPPA-shareGPT
Methodology:
Fine-tuned using bagel on TinyLlama
Input Output 
Input Format:
Multiple prompt formats used: vicuna, llama-2, alpaca, and chat-ml
Performance Tips:
Recommend only 1 epoch of training during fine-tuning.
LLM NameBagel 1.1B V0.3
Repository 🤗https://huggingface.co/jondurbin/bagel-1.1b-v0.3 
Model Size1.1b
Required VRAM2.2 GB
Updated2025-08-18
Maintainerjondurbin
Model Typellama
Model Files  2.2 GB
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than jondurbin/bagel-1.1b-v0.3.

Rank the Bagel 1.1B V0.3 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 v20241124
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