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README.md
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---
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language:
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- en
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- zh
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license: apache-2.0
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library_name: transformers
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tags:
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- chat
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- conversational
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- custom-research
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- rp
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- roleplay
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- tool-use
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base_model:
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- Qwen/Qwen2.5-14B-Instruct
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pipeline_tag: text-generation
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model-index:
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- name: miscii-14b-1028
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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: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 82.37
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name: strict accuracy
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source:
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url: >-
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
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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: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 49.26
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name: normalized accuracy
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+
source:
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url: >-
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+
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
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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: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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+
metrics:
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- type: exact_match
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value: 6.34
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name: exact match
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+
source:
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url: >-
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+
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
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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: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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+
metrics:
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- type: acc_norm
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value: 14.21
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name: acc_norm
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+
source:
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url: >-
|
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+
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
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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: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 12
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name: acc_norm
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source:
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url: >-
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+
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
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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-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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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: 46.14
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name: accuracy
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source:
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url: >-
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sthenno-com/miscii-14b-1028
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name: Open LLM Leaderboard
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datasets:
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- nvidia/HelpSteer2
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- google/Synthetic-Persona-Chat
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- mlabonne/orpo-dpo-mix-40k
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---
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[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
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# QuantFactory/miscii-14b-1028-GGUF
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This is quantized version of [sthenno-com/miscii-14b-1028](https://huggingface.co/sthenno-com/miscii-14b-1028) created using llama.cpp
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# Original Model Card
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# miscii-14b-1028
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## Role-based Instructions
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Just parse the following as your system prompt.
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Note there is NO `special-tokens` here.
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```python
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system_prompt: str = (
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"""<|context_start|>personas
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<|user_persona_start|>statement
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{user_persona}<|user_persona_end|>
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<|assistant_persona_start|>statement
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{assistant_persona}<|assistant_persona_end|><|context_end|>""".format(
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user_persona="""I am Miscii. # example
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<optional: personal statement, e.g. I am the designer of Sthenno.>
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<optional: additional statements>""",
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assistant_persona="""I am Sthenno. # example
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<optional: personal statement, e.g. I speak in Chinese.>
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<optional: additional statements>""",
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)
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)
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```
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## Training
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See [Report for miscii-1020](https://api.wandb.ai/links/flandrelabs-carnegie-mellon-university/p35vchzx) for more details.
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-----
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_sthenno-com__miscii-14b-1028)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |35.05|
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|IFEval (0-Shot) |82.37|
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|BBH (3-Shot) |49.26|
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|MATH Lvl 5 (4-Shot)| 6.34|
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|GPQA (0-shot) |14.21|
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|MuSR (0-shot) |12.00|
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|MMLU-PRO (5-shot) |46.14|
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$$\large{\text{There's nothing more to Show}}$$
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