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Model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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model-index:
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- name: OpenHermes-2.5-neural-chat-v3-3-Slerp
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 68.09
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name: normalized accuracy
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 86.2
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name: normalized accuracy
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 64.26
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name: accuracy
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 62.78
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 79.16
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name: accuracy
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 67.78
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name: accuracy
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tags:
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- merge
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base_model:
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- teknium/OpenHermes-2.5-Mistral-7B
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- Intel/neural-chat-7b-v3-3
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---
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# OpenHermes-2.5-neural-chat-v3-3-Slerp
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This is the model for OpenHermes-2.5-neural-chat-v3-3-Slerp. I used [mergekit](https://github.com/cg123/mergekit) to merge models.
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# Prompt Templates
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You can use these prompt templates, but I recommend using ChatML.
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### ChatML [(OpenHermes-2.5-Mistral-7B)](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B):
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```
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<|im_start|>system
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{system}<|im_end|>
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<|im_start|>user
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{user}<|im_end|>
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<|im_start|>assistant
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{asistant}<|im_end|>
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```
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### [neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3):
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```
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### System:
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{system}
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### User:
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{user}
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### Assistant:
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```
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# Yaml Config to reproduce
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```yaml
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slices:
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- sources:
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- model: teknium/OpenHermes-2.5-Mistral-7B
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layer_range: [0, 32]
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- model: Intel/neural-chat-7b-v3-3
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layer_range: [0, 32]
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merge_method: slerp
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base_model: mistralai/Mistral-7B-v0.1
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5 # fallback for rest of tensors
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dtype: bfloat16
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```
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# Quantizationed versions
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Quantizationed versions of this model is available thanks to [TheBloke](https://hf.co/TheBloke).
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##### GPTQ
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- [TheBloke/OpenHermes-2.5-neural-chat-v3-3-Slerp-GPTQ](https://huggingface.co/TheBloke/OpenHermes-2.5-neural-chat-v3-3-Slerp-GPTQ)
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##### GGUF
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- [TheBloke/OpenHermes-2.5-neural-chat-v3-3-Slerp-GGUF](https://huggingface.co/TheBloke/OpenHermes-2.5-neural-chat-v3-3-Slerp-GGUF)
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##### AWQ
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- [TheBloke/OpenHermes-2.5-neural-chat-v3-3-Slerp-AWQ](https://huggingface.co/TheBloke/OpenHermes-2.5-neural-chat-v3-3-Slerp-AWQ)
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_PulsarAI__OpenHermes-2.5-neural-chat-v3-3-Slerp)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 71.38 |
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| ARC (25-shot) | 68.09 |
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| HellaSwag (10-shot) | 86.2 |
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| MMLU (5-shot) | 64.26 |
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| TruthfulQA (0-shot) | 62.78 |
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| Winogrande (5-shot) | 79.16 |
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| GSM8K (5-shot) | 67.78 |
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If you would like to support me:
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[☕ Buy Me a Coffee](https://www.buymeacoffee.com/weyaxi)
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