56 lines
1.5 KiB
Markdown
56 lines
1.5 KiB
Markdown
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---
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license: other
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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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- AWQ
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- text-generation
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- autotrain_compatible
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- endpoints_compatible
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- generated_from_trainer
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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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datasets:
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- cognitivecomputations/Dolphin-2.9
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- teknium/OpenHermes-2.5
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- m-a-p/CodeFeedback-Filtered-Instruction
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- cognitivecomputations/dolphin-coder
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- cognitivecomputations/samantha-data
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- HuggingFaceH4/ultrachat_200k
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- microsoft/orca-math-word-problems-200k
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- abacusai/SystemChat-1.1
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- Locutusque/function-calling-chatml
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- internlm/Agent-FLAN
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---
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# cognitivecomputations/dolphin-2.9-llama3-8b AWQ
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Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations
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Discord: https://discord.gg/8fbBeC7ZGx
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />
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My appreciation for the sponsors of Dolphin 2.9:
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- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 10xL40S node
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This model is based on Llama-3-8b, and is governed by [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](LICENSE)
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The base model has 8k context, and the full-weight fine-tuning was with 4k sequence length.
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It took 2.5 days on 8x L40S provided by Crusoe Cloud
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This model was trained FFT on all parameters, using ChatML prompt template format.
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example:
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```
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<|im_start|>system
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You are Dolphin, a helpful AI assistant.<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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```
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