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README.md ADDED
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+ ---
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+ language:
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+ - en
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+ license: apache-2.0
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+ tags:
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+ - smol_llama
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+ - llama2
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+ datasets:
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+ - JeanKaddour/minipile
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+ - pszemraj/simple_wikipedia_LM
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+ - mattymchen/refinedweb-3m
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+ - BEE-spoke-data/knowledge-inoc-concat-v1
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+ inference:
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+ parameters:
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+ max_new_tokens: 64
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+ do_sample: true
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+ temperature: 0.8
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+ repetition_penalty: 1.05
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+ no_repeat_ngram_size: 4
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+ eta_cutoff: 0.0006
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+ renormalize_logits: true
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+ widget:
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+ - text: My name is El Microondas the Wise, and
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+ example_title: El Microondas
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+ - text: Kennesaw State University is a public
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+ example_title: Kennesaw State University
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+ - text: Bungie Studios is an American video game developer. They are most famous for
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+ developing the award winning Halo series of video games. They also made Destiny.
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+ The studio was founded
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+ example_title: Bungie
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+ - text: The Mona Lisa is a world-renowned painting created by
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+ example_title: Mona Lisa
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+ - text: The Harry Potter series, written by J.K. Rowling, begins with the book titled
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+ example_title: Harry Potter Series
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+ - text: 'Question: I have cities, but no houses. I have mountains, but no trees. I
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+ have water, but no fish. What am I?
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+
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+ Answer:'
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+ example_title: Riddle
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+ - text: The process of photosynthesis involves the conversion of
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+ example_title: Photosynthesis
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+ - text: Jane went to the store to buy some groceries. She picked up apples, oranges,
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+ and a loaf of bread. When she got home, she realized she forgot
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+ example_title: Story Continuation
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+ - text: 'Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph,
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+ and another train leaves Station B at 10:00 AM and travels at 80 mph, when will
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+ they meet if the distance between the stations is 300 miles?
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+
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+ To determine'
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+ example_title: Math Problem
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+ - text: In the context of computer programming, an algorithm is
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+ example_title: Algorithm Definition
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+ pipeline_tag: text-generation
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+ model-index:
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+ - name: smol_llama-220M-GQA
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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: 24.83
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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=BEE-spoke-data/smol_llama-220M-GQA
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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: 29.76
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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=BEE-spoke-data/smol_llama-220M-GQA
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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: 25.85
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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=BEE-spoke-data/smol_llama-220M-GQA
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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: 44.55
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-GQA
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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: 50.99
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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=BEE-spoke-data/smol_llama-220M-GQA
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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: 0.68
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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=BEE-spoke-data/smol_llama-220M-GQA
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+ name: Open LLM Leaderboard
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+ ---
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+
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+
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+ # smol_llama: 220M GQA
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+
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+ > model card WIP, more details to come
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+
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+
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+ A small 220M param (total) decoder model. This is the first version of the model.
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+
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+ - 1024 hidden size, 10 layers
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+ - GQA (32 heads, 8 key-value), context length 2048
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+ - train-from-scratch on one GPU :)
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+
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+ ## Links
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+
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+ [Here](https://huggingface.co/collections/BEE-spoke-data/finetuned-smol-220m-65998b080ae723e79c830f83) are some fine-tunes we did, but there are many more possibilities out there!
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+
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+ - instruct
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+ - openhermes - [link](https://huggingface.co/BEE-spoke-data/smol_llama-220M-openhermes)
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+ - open-instruct - [link](https://huggingface.co/BEE-spoke-data/smol_llama-220M-open_instruct)
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+ - code
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+ - python (pypi) - [link](https://huggingface.co/BEE-spoke-data/beecoder-220M-python)
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+ - zephyr DPO tune
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+ - SFT - [link](https://huggingface.co/BEE-spoke-data/zephyr-220m-sft-full)
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+ - full DPO - [link](https://huggingface.co/BEE-spoke-data/zephyr-220m-dpo-full)
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+
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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)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_BEE-spoke-data__smol_llama-220M-GQA)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |29.44|
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+ |AI2 Reasoning Challenge (25-Shot)|24.83|
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+ |HellaSwag (10-Shot) |29.76|
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+ |MMLU (5-Shot) |25.85|
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+ |TruthfulQA (0-shot) |44.55|
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+ |Winogrande (5-shot) |50.99|
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+ |GSM8k (5-shot) | 0.68|
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+
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+ "_name_or_path": "BEE-spoke-data/NanoLlama-GQA-L10-A32_KV8-v17-KI",
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