--- license: llama3 library_name: transformers tags: - mergekit - merge base_model: - nbeerbower/llama3.1-gutenberg-8B - akjindal53244/Llama-3.1-Storm-8B - NousResearch/Meta-Llama-3.1-8B - nbeerbower/llama3.1-airoboros3.2-QDT-8B - Sao10K/Llama-3.1-8B-Stheno-v3.4 model-index: - name: Llama-3.1-8B-Ultra-Instruct results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 80.81 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 32.49 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 14.95 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 5.59 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 8.61 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 31.4 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct name: Open LLM Leaderboard --- ![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ) # QuantFactory/Llama-3.1-8B-Ultra-Instruct-GGUF This is quantized version of [Dampfinchen/Llama-3.1-8B-Ultra-Instruct](https://huggingface.co/Dampfinchen/Llama-3.1-8B-Ultra-Instruct) created using llama.cpp # Original Model Card # merge This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## Merge Details ### Merge Method This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [NousResearch/Meta-Llama-3.1-8B](https://huggingface.co/NousResearch/Meta-Llama-3.1-8B) as a base. ### Models Merged The following models were included in the merge: * [nbeerbower/llama3.1-gutenberg-8B](https://huggingface.co/nbeerbower/llama3.1-gutenberg-8B) * [akjindal53244/Llama-3.1-Storm-8B](https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B) * [nbeerbower/llama3.1-airoboros3.2-QDT-8B](https://huggingface.co/nbeerbower/llama3.1-airoboros3.2-QDT-8B) * [Sao10K/Llama-3.1-8B-Stheno-v3.4](https://huggingface.co/Sao10K/Llama-3.1-8B-Stheno-v3.4) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: Sao10K/Llama-3.1-8B-Stheno-v3.4 parameters: weight: 0.2 density: 0.5 - model: akjindal53244/Llama-3.1-Storm-8B parameters: weight: 0.5 density: 0.5 - model: nbeerbower/llama3.1-gutenberg-8B parameters: weight: 0.3 density: 0.5 - model: nbeerbower/llama3.1-airoboros3.2-QDT-8B parameters: weight: 0.2 density: 0.5 merge_method: dare_ties base_model: NousResearch/Meta-Llama-3.1-8B dtype: bfloat16 name: Llama-3.1-8B-Ultra-Instruct ``` Use Llama 3 Instruct prompt template. Use with caution, I'm not responsible for what you do with it. All credits and thanks go to the creators of the fine tunes I've merged. In my own tests and on HF Eval it performs very well for a 8B model and I can recommend it. High quality quants by Bartowski: https://huggingface.co/bartowski/Llama-3.1-8B-Ultra-Instruct-GGUF # [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_Dampfinchen__Llama-3.1-8B-Ultra-Instruct) | Metric |Value| |-------------------|----:| |Avg. |28.98| |IFEval (0-Shot) |80.81| |BBH (3-Shot) |32.49| |MATH Lvl 5 (4-Shot)|14.95| |GPQA (0-shot) | 5.59| |MuSR (0-shot) | 8.61| |MMLU-PRO (5-shot) |31.40|