Create README.md
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README.md
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---
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license: apache-2.0
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language:
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- en
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---
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<div align="center">
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# TinyMix-8x1b
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</div>
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This is a MoE-ification of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) using the [Mixtral branch of mergekit](https://github.com/cg123/mergekit)
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The Goal was to MoE-fy the TinyLlama model and then use this as a base model to further train from. The intuition being finetuning 8x1b should give better performance than finetuning 1b by itself.
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More work coming!
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# Inference Template
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This is a merge of the base model, so treat it like a completion.
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```
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llm.generate('Quantum Tunneling is')
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```
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## Mergekit Config
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```
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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gate_mode: hidden
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dtype: bfloat16
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experts:
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- source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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positive_prompts: [""]
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- source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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positive_prompts: [""]
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- source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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positive_prompts: [""]
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- source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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positive_prompts: [""]
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- source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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positive_prompts: [""]
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- source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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positive_prompts: [""]
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- source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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positive_prompts: [""]
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- source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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positive_prompts: [""]
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```
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# Eval
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Thanks to u/mhenrichsen for thr HellaSwag score
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```
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| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
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|---------|-------|------|-----:|--------|-----:|---|-----:|
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|hellaswag|Yaml |none | 0|acc |0.4659|± |0.0050|
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| | |none | 0|acc\_norm|0.6044|± |0.0049|
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```
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