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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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tags:
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- axolotl
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- generated_from_trainer
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- Mistral
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- instruct
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- finetune
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- chatml
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- gpt4
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- synthetic data
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- science
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- physics
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- chemistry
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- biology
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- math
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- llama-cpp
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- gguf-my-repo
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base_model: mistralai/Mistral-7B-v0.1
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datasets:
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- allenai/ai2_arc
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- camel-ai/physics
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- camel-ai/chemistry
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- camel-ai/biology
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- camel-ai/math
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- metaeval/reclor
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- openbookqa
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- mandyyyyii/scibench
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- derek-thomas/ScienceQA
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- TIGER-Lab/ScienceEval
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- jondurbin/airoboros-3.2
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- LDJnr/Capybara
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- Cot-Alpaca-GPT4-From-OpenHermes-2.5
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- STEM-AI-mtl/Electrical-engineering
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- knowrohit07/saraswati-stem
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- sablo/oasst2_curated
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- glaiveai/glaive-code-assistant
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- lmsys/lmsys-chat-1m
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- TIGER-Lab/MathInstruct
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- bigbio/med_qa
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- meta-math/MetaMathQA-40K
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- openbookqa
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- piqa
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- metaeval/reclor
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- derek-thomas/ScienceQA
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- scibench
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- sciq
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- Open-Orca/SlimOrca
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- migtissera/Synthia-v1.3
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- TIGER-Lab/ScienceEval
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model-index:
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- name: Einstein-v4-7B
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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: 64.68
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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=Weyaxi/Einstein-v4-7B
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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:
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- type: acc_norm
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value: 83.75
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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=Weyaxi/Einstein-v4-7B
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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:
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- type: acc
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value: 62.31
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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=Weyaxi/Einstein-v4-7B
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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:
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- type: mc2
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value: 55.15
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
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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:
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- type: acc
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value: 76.24
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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=Weyaxi/Einstein-v4-7B
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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:
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- type: acc
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value: 57.62
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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=Weyaxi/Einstein-v4-7B
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name: Open LLM Leaderboard
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---
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# DavidAU/Einstein-v4-7B-Q8_0-GGUF
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This model was converted to GGUF format from [`Weyaxi/Einstein-v4-7B`](https://huggingface.co/Weyaxi/Einstein-v4-7B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/Weyaxi/Einstein-v4-7B) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew.
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```bash
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brew install ggerganov/ggerganov/llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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CLI:
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```bash
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llama-cli --hf-repo DavidAU/Einstein-v4-7B-Q8_0-GGUF --model einstein-v4-7b.Q8_0.gguf -p "The meaning to life and the universe is"
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```
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Server:
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```bash
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llama-server --hf-repo DavidAU/Einstein-v4-7B-Q8_0-GGUF --model einstein-v4-7b.Q8_0.gguf -c 2048
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```
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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
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```
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git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make && ./main -m einstein-v4-7b.Q8_0.gguf -n 128
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```
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