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Bagel 8B V1.0 by jondurbin

 »  All LLMs  »  jondurbin  »  Bagel 8B V1.0   URL Share it on

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  Autotrain compatible   Bagel Base model:finetune:meta-llama... Base model:meta-llama/meta-lla...   Conversational   Dataset:ai2 arc Dataset:allenai/ultrafeedback ... Dataset:argilla/distilabel-int... Dataset:b-mc2/sql-create-conte... Dataset:bluemoon-fandom-1-1-rp...   Dataset:boolq   Dataset:cakiki/rosetta-code   Dataset:camel-ai/biology   Dataset:camel-ai/chemistry   Dataset:camel-ai/math   Dataset:camel-ai/physics   Dataset:codeparrot/apps   Dataset:facebook/belebele Dataset:glaiveai/glaive-functi... Dataset:grimulkan/limarp-augme... Dataset:jondurbin/airoboros-3.... Dataset:jondurbin/cinematika-v... Dataset:jondurbin/contextual-d... Dataset:jondurbin/gutenberg-dp...   Dataset:jondurbin/py-dpo-v0.1 Dataset:jondurbin/truthy-dpo-v...   Dataset:kingbri/pippa-sharegpt   Dataset:ldjnr/capybara   Dataset:lmsys/lmsys-chat-1m Dataset:mattpscott/airoboros-s... Dataset:migtissera/synthia-v1.... Dataset:muennighoff/natural-in...   Dataset:open-orca/slimorca   Dataset:openbookqa Dataset:parisneo/lollms aware ...   Dataset:piqa   Dataset:ropes   Dataset:squad v2   Dataset:tiger-lab/mathinstruct Dataset:unalignment/toxic-dpo-... Dataset:vezora/tested-22k-pyth... Dataset:whiterabbitneo/wrn-cha... Dataset:whiterabbitneo/wrn-cha...   Dataset:winogrande Dataset:wizardlm/wizardlm evol...   Endpoints compatible   Instruct   Llama   Llama-3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/jondurbin/bagel-8b-v1.0 

Bagel 8B V1.0 Benchmarks

ARC: 65.44 vs 96.7 (so35)-32.3%
HellaSwag: 82.37 vs 95.3 (gpt4)-13.6%
MMLU: 67.81 vs 88.3 (so35)-23.2%
TruthfulQA: 54.43 vs 59 (gpt4)-7.7%
WinoGrande: 79.01 vs 87.5 (gpt4)-9.7%
GSM8K: 58 vs 96.4 (so35)-39.8%
LLME Score: 0.24236
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bagel 8B V1.0 (jondurbin/bagel-8b-v1.0)

Bagel 8B V1.0 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
research, commercial applications
Applications:
text generation, roleplay assistance
Primary Use Cases:
novel writing, question answering, summarization
Limitations:
potential ethical and misuse issues
Considerations:
Use responsibly, especially in areas of sensitive data.
Additional Notes 
The model is highly adaptable with various prompt styles available.
Training Details 
Data Sources:
ai2_arc, airoboros, apps, belebele, bluemoon, boolq, camel-ai biology, camel-ai chemistry, camel-ai math, camel-ai physics, capybara, cinematika, emobank, evol-instruct, glaive-function-calling-v2, gutenberg, limarp-augmented, lmsys_chat_1m, lollms, mathinstruct, natural_instructions, openbookqa, pippa, piqa, python_alpaca, ropes, rosetta_code, slimorca, sql-create-context, squad_v2, airoboros-summarization, synthia, whiterabbitneo chapter 1, whiterabbitneo chapter 2, winogrande
Input Output 
Input Format:
llama-3-instruct
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Use low temperature for more deterministic answers.
LLM NameBagel 8B V1.0
Repository 🤗https://huggingface.co/jondurbin/bagel-8b-v1.0 
Base Model(s)  Meta Llama 3 8B   meta-llama/Meta-Llama-3-8B
Model Size8b
Required VRAM16.1 GB
Updated2025-02-22
Maintainerjondurbin
Model Typellama
Instruction-BasedYes
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
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.41.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128256
Torch Data Typebfloat16

Quantized Models of the Bagel 8B V1.0

Model
Likes
Downloads
VRAM
Bagel 8B V1.0 AWQ0845 GB

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MrRoboto ProLong 8B V2a1024K / 16.1 GB1020
Note: green Score (e.g. "73.2") means that the model is better than jondurbin/bagel-8b-v1.0.

Rank the Bagel 8B V1.0 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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