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Model: lodrick-the-lafted/Grafted-Hermetic-Platypus-D-2x7B 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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datasets:
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- lodrick-the-lafted/Hermes-40K
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- garage-bAInd/Open-Platypus
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- jondurbin/airoboros-3.2
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model-index:
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- name: Grafted-Hermetic-Platypus-D-2x7B
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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: 58.87
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lodrick-the-lafted/Grafted-Hermetic-Platypus-D-2x7B
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name: Open LLM Leaderboard
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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: 82.89
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lodrick-the-lafted/Grafted-Hermetic-Platypus-D-2x7B
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name: Open LLM Leaderboard
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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: 61.96
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lodrick-the-lafted/Grafted-Hermetic-Platypus-D-2x7B
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name: Open LLM Leaderboard
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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: 61.02
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lodrick-the-lafted/Grafted-Hermetic-Platypus-D-2x7B
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name: Open LLM Leaderboard
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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: 77.43
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lodrick-the-lafted/Grafted-Hermetic-Platypus-D-2x7B
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name: Open LLM Leaderboard
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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: 43.29
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=lodrick-the-lafted/Grafted-Hermetic-Platypus-D-2x7B
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name: Open LLM Leaderboard
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---
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<img src=https://huggingface.co/lodrick-the-lafted/Grafted-Hermetic-Platypus-D-2x7B/resolve/main/ghp.png>
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# Grafted-Hermetic-Platypus-D-2x7B
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MoE merge of
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- [Platyboros-Instruct-7B](https://huggingface.co/lodrick-the-lafted/Platyboros-Instruct-7B)
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- [Hermes-Instruct-7B-v0.2](https://huggingface.co/lodrick-the-lafted/Hermes-Instruct-7B-v0.2)
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Basically the same thing as GHP-A.
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<br />
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<br />
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# Prompt Format
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Both the default Mistral-Instruct tags and Alpaca are fine, so either:
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```
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<s>[INST] {sys_prompt} {instruction} [/INST]
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```
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or
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```
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{sys_prompt}
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### Instruction:
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{instruction}
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### Response:
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```
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The tokenizer default is Alpaca this time around.
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<br />
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<br />
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# Usage
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```python
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "lodrick-the-lafted/Grafted-Hermetic-Platypus-A-2x7B"
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tokenizer = AutoTokenizer.from_pretrained(model)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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model_kwargs={"torch_dtype": torch.bfloat16},
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)
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messages = [{"role": "user", "content": "Give me a cooking recipe for an pumpkin pie."}]
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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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_lodrick-the-lafted__Grafted-Hermetic-Platypus-D-2x7B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |64.24|
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|AI2 Reasoning Challenge (25-Shot)|58.87|
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|HellaSwag (10-Shot) |82.89|
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|MMLU (5-Shot) |61.96|
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|TruthfulQA (0-shot) |61.02|
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|Winogrande (5-shot) |77.43|
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|GSM8k (5-shot) |43.29|
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