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README.md
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---
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library_name: transformers
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tags:
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- 4-bit
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- text-generation
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- autotrain_compatible
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- endpoints_compatible
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pipeline_tag: text-generation
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inference: false
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quantized_by: Suparious
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- Model creator: [jondurbin](https://huggingface.co/jondurbin)
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- Original model: [bagel-8b-v1.0](https://huggingface.co/jondurbin/bagel-8b-v1.0)
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## How to use
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---
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license: other
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license_name: llama3
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license_link: https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE
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base_model: meta-llama/Meta-Llama-3-8B
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library_name: transformers
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tags:
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- 4-bit
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- text-generation
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- autotrain_compatible
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- endpoints_compatible
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- llama-3
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- bagel
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datasets:
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- ai2_arc
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- allenai/ultrafeedback_binarized_cleaned
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- argilla/distilabel-intel-orca-dpo-pairs
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- jondurbin/airoboros-3.2
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- codeparrot/apps
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- facebook/belebele
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- bluemoon-fandom-1-1-rp-cleaned
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- boolq
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- camel-ai/biology
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- camel-ai/chemistry
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- camel-ai/math
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- camel-ai/physics
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- jondurbin/contextual-dpo-v0.1
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- jondurbin/gutenberg-dpo-v0.1
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- jondurbin/py-dpo-v0.1
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- jondurbin/truthy-dpo-v0.1
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- LDJnr/Capybara
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- jondurbin/cinematika-v0.1
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- WizardLM/WizardLM_evol_instruct_70k
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- glaiveai/glaive-function-calling-v2
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- jondurbin/gutenberg-dpo-v0.1
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- grimulkan/LimaRP-augmented
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- lmsys/lmsys-chat-1m
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- ParisNeo/lollms_aware_dataset
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- TIGER-Lab/MathInstruct
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- Muennighoff/natural-instructions
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- openbookqa
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- kingbri/PIPPA-shareGPT
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- piqa
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- Vezora/Tested-22k-Python-Alpaca
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- ropes
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- cakiki/rosetta-code
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- Open-Orca/SlimOrca
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- b-mc2/sql-create-context
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- squad_v2
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- mattpscott/airoboros-summarization
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- migtissera/Synthia-v1.3
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- unalignment/toxic-dpo-v0.2
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- WhiteRabbitNeo/WRN-Chapter-1
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- WhiteRabbitNeo/WRN-Chapter-2
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- winogrande
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pipeline_tag: text-generation
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inference: false
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quantized_by: Suparious
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- Model creator: [jondurbin](https://huggingface.co/jondurbin)
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- Original model: [bagel-8b-v1.0](https://huggingface.co/jondurbin/bagel-8b-v1.0)
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## Model Summary
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The name of this model is "llama-3-bagel-8b-v1.0" and it was built with llama-3 from Meta.
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This is a fine-tune of llama-3-8b using the bagel dataset, but instead of 4 prompt formats it's standardized on a single format - llama-3 instruct.
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See [bagel](https://github.com/jondurbin/bagel) for additional details on the datasets.
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## How to use
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