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Model: pankajmathur/orca_mini_v3_7b Source: Original Platform
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398
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README.md
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---
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language:
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- en
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license: other
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library_name: transformers
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datasets:
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- psmathur/orca_mini_v1_dataset
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- ehartford/dolphin
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pipeline_tag: text-generation
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model-index:
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- name: orca_mini_v3_7b
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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: 56.91
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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=psmathur/orca_mini_v3_7b
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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:
|
||||
- type: acc_norm
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value: 79.64
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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=psmathur/orca_mini_v3_7b
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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:
|
||||
- type: acc
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value: 52.37
|
||||
name: accuracy
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source:
|
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=psmathur/orca_mini_v3_7b
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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:
|
||||
- type: mc2
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value: 50.51
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||||
source:
|
||||
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=psmathur/orca_mini_v3_7b
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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:
|
||||
- type: acc
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||||
value: 74.27
|
||||
name: accuracy
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||||
source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=psmathur/orca_mini_v3_7b
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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:
|
||||
- type: acc
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||||
value: 7.13
|
||||
name: accuracy
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||||
source:
|
||||
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=psmathur/orca_mini_v3_7b
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name: Open LLM Leaderboard
|
||||
- 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: 28.21
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||||
name: strict accuracy
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||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/orca_mini_v3_7b
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name: Open LLM Leaderboard
|
||||
- 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:
|
||||
- type: acc_norm
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||||
value: 17.84
|
||||
name: normalized accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/orca_mini_v3_7b
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
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type: text-generation
|
||||
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
|
||||
args:
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num_few_shot: 4
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metrics:
|
||||
- type: exact_match
|
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value: 0.3
|
||||
name: exact match
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/orca_mini_v3_7b
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
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dataset:
|
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
|
||||
args:
|
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num_few_shot: 0
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||||
metrics:
|
||||
- type: acc_norm
|
||||
value: 0.0
|
||||
name: acc_norm
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/orca_mini_v3_7b
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
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type: text-generation
|
||||
name: Text Generation
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||||
dataset:
|
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
|
||||
args:
|
||||
num_few_shot: 0
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metrics:
|
||||
- type: acc_norm
|
||||
value: 22.71
|
||||
name: acc_norm
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/orca_mini_v3_7b
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
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type: text-generation
|
||||
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:
|
||||
- type: acc
|
||||
value: 12.04
|
||||
name: accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/orca_mini_v3_7b
|
||||
name: Open LLM Leaderboard
|
||||
---
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# orca_mini_v3_7b
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A LLama2-7b model trained on Orca Style datasets.
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<br>
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<br>
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🤔 How good is orca-mini-v3-7b? Do the evaluation results from HuggingFace Open LLM leaderboard translate to real-world use cases?
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🔍 Now you can figure it out for yourself!
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Introducing the orca-mini chatbot powered by the orca-mini-v3-7b model. Dive in and see how the open source 7b model stacks up in the world of massive language models. 🌍
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⏰ Hurry up before I run out of GPU credits! 😉
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Check it out here 👉
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[https://huggingface.co/spaces/psmathur/psmathur-orca_mini_v3_7b](https://huggingface.co/spaces/psmathur/psmathur-orca_mini_v3_7b)
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<br>
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**P.S. If you're interested to collaborate, please connect with me at www.linkedin.com/in/pankajam.**
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<br>
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### quantized versions
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Big thanks to [@TheBloke](https://huggingface.co/TheBloke)
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|
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1) https://huggingface.co/TheBloke/orca_mini_v3_7B-GGML
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|
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2) https://huggingface.co/TheBloke/orca_mini_v3_7B-GPTQ
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<br>
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#### license disclaimer:
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This model is bound by the license & usage restrictions of the original Llama-2 model. And comes with no warranty or gurantees of any kind.
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<br>
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## evaluation
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We evaluated orca_mini_v3_7b on a wide range of tasks using [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) from EleutherAI.
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Here are the results on metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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|||||
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|:------:|:--------:|:-------:|:--------:|
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|**Task**|**Metric**|**Value**|**Stderr**|
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|*arc_challenge*|acc_norm|0.5717|0.0145|
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|*hellaswag*|acc_norm|0.7966|0.0043|
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|*mmlu*|acc_norm|0.5234|0.035|
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|*truthfulqa_mc*|mc2|0.5029|0.0156|
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|**Total Average**|-|**0.59865**||
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<br>
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## example esage
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Here is prompt format
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```
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### System:
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You are an AI assistant that follows instruction extremely well. Help as much as you can.
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### User:
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Tell me about Orcas.
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### Assistant:
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```
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Below shows a code example on how to use this model
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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tokenizer = AutoTokenizer.from_pretrained("psmathur/orca_mini_v3_7b", use_fast=False)
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model = AutoModelForCausalLM.from_pretrained(
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"psmathur/orca_mini_v3_7b",
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torch_dtype=torch.float16,
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load_in_8bit=True,
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low_cpu_mem_usage=True,
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device_map="auto"
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)
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system_prompt = "### System:\nYou are an AI assistant that follows instruction extremely well. Help as much as you can.\n\n"
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#generate text steps
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instruction = "Tell me about Orcas."
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prompt = f"{system_prompt}### User: {instruction}\n\n### Assistant:\n"
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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output = model.generate(**inputs, do_sample=True, top_p=0.95, top_k=0, max_new_tokens=4096)
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print(tokenizer.decode(output[0], skip_special_tokens=True))
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```
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<br>
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#### limitations & biases:
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While this model aims for accuracy, it can occasionally produce inaccurate or misleading results.
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Despite diligent efforts in refining the pretraining data, there remains a possibility for the generation of inappropriate, biased, or offensive content.
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Exercise caution and cross-check information when necessary.
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<br>
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### citiation:
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Please kindly cite using the following BibTeX:
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```
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@misc{orca_mini_v3_7b,
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author = {Pankaj Mathur},
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title = {orca_mini_v3_7b: An explain tuned Llama2-7b model},
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year = {2023},
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publisher = {GitHub, HuggingFace},
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journal = {GitHub repository, HuggingFace repository},
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howpublished = {\url{https://https://huggingface.co/psmathur/orca_mini_v3_7b},
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}
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```
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```
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@misc{mukherjee2023orca,
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title={Orca: Progressive Learning from Complex Explanation Traces of GPT-4},
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author={Subhabrata Mukherjee and Arindam Mitra and Ganesh Jawahar and Sahaj Agarwal and Hamid Palangi and Ahmed Awadallah},
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year={2023},
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eprint={2306.02707},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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|
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```
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@software{touvron2023llama,
|
||||
title={LLaMA2: Open and Efficient Foundation Language Models},
|
||||
author={Touvron, Hugo and Lavril, Thibaut and Izacard, Gautier and Martinet, Xavier and Lachaux, Marie-Anne and Lacroix, Timoth{\'e}e and Rozi{\`e}re, Baptiste and Goyal, Naman and Hambro, Eric and Azhar, Faisal and Rodriguez, Aurelien and Joulin, Armand and Grave, Edouard and Lample, Guillaume},
|
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journal={arXiv preprint arXiv:2302.13971},
|
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year={2023}
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}
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
|
||||
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_psmathur__orca_mini_v3_7b)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 47.98 |
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| ARC (25-shot) | 56.91 |
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| HellaSwag (10-shot) | 79.64 |
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| MMLU (5-shot) | 52.37 |
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| TruthfulQA (0-shot) | 50.51 |
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| Winogrande (5-shot) | 74.27 |
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| GSM8K (5-shot) | 7.13 |
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| DROP (3-shot) | 15.06 |
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|
||||
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
|
||||
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_psmathur__orca_mini_v3_7b)
|
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| Metric |Value|
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||||
|---------------------------------|----:|
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|Avg. |53.47|
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|AI2 Reasoning Challenge (25-Shot)|56.91|
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|HellaSwag (10-Shot) |79.64|
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|MMLU (5-Shot) |52.37|
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|TruthfulQA (0-shot) |50.51|
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|Winogrande (5-shot) |74.27|
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|GSM8k (5-shot) | 7.13|
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||||
|
||||
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
|
||||
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_pankajmathur__orca_mini_v3_7b)
|
||||
|
||||
| Metric |Value|
|
||||
|-------------------|----:|
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||||
|Avg. |13.52|
|
||||
|IFEval (0-Shot) |28.21|
|
||||
|BBH (3-Shot) |17.84|
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||||
|MATH Lvl 5 (4-Shot)| 0.30|
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|GPQA (0-shot) | 0.00|
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|MuSR (0-shot) |22.71|
|
||||
|MMLU-PRO (5-shot) |12.04|
|
||||
|
||||
26
config.json
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26
config.json
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@@ -0,0 +1,26 @@
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||||
{
|
||||
"_name_or_path": "TheBloke/Llama-2-7B-fp16",
|
||||
"architectures": [
|
||||
"LlamaForCausalLM"
|
||||
],
|
||||
"bos_token_id": 1,
|
||||
"eos_token_id": 2,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 4096,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 11008,
|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
"model.layers.8.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.8.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
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|
||||
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|
||||
"model.layers.9.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
"model.norm.weight": "pytorch_model-00002-of-00002.bin"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
93391
tokenizer.json
Normal file
93391
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
3
tokenizer.model
Normal file
3
tokenizer.model
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
|
||||
size 499723
|
||||
31
tokenizer_config.json
Normal file
31
tokenizer_config.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"model_max_length": 4096,
|
||||
"pad_token": null,
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user