--- base_model: nbeerbower/Hermes2-Gutenberg2-Mistral-7B datasets: - jondurbin/gutenberg-dpo-v0.1 - nbeerbower/gutenberg2-dpo library_name: transformers license: apache-2.0 tags: - llama-cpp - gguf-my-repo model-index: - name: Hermes2-Gutenberg2-Mistral-7B 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: 37.21 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Hermes2-Gutenberg2-Mistral-7B 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: 28.91 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Hermes2-Gutenberg2-Mistral-7B 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: 5.66 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Hermes2-Gutenberg2-Mistral-7B 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: 5.26 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Hermes2-Gutenberg2-Mistral-7B 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: 16.92 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Hermes2-Gutenberg2-Mistral-7B 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: 22.14 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Hermes2-Gutenberg2-Mistral-7B name: Open LLM Leaderboard --- # Triangle104/Hermes2-Gutenberg2-Mistral-7B-Q4_K_S-GGUF This model was converted to GGUF format from [`nbeerbower/Hermes2-Gutenberg2-Mistral-7B`](https://huggingface.co/nbeerbower/Hermes2-Gutenberg2-Mistral-7B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/nbeerbower/Hermes2-Gutenberg2-Mistral-7B) for more details on the model. --- Model details: - Hermes2-Gutenberg2-Mistral-7B NousResearch/Hermes-2-Pro-Mistral-7B finetuned on jondurbin/gutenberg-dpo-v0.1 and nbeerbower/gutenberg2-dpo. Method ORPO tuned with 2x RTX 3090 for 3 epochs. Open LLM Leaderboard Evaluation Results Detailed results can be found here Metric Value Avg. 19.35 IFEval (0-Shot) 37.21 BBH (3-Shot) 28.91 MATH Lvl 5 (4-Shot) 5.66 GPQA (0-shot) 5.26 MuSR (0-shot) 16.92 MMLU-PRO (5-shot) 22.14 --- ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo Triangle104/Hermes2-Gutenberg2-Mistral-7B-Q4_K_S-GGUF --hf-file hermes2-gutenberg2-mistral-7b-q4_k_s.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Triangle104/Hermes2-Gutenberg2-Mistral-7B-Q4_K_S-GGUF --hf-file hermes2-gutenberg2-mistral-7b-q4_k_s.gguf -c 2048 ``` 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. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo Triangle104/Hermes2-Gutenberg2-Mistral-7B-Q4_K_S-GGUF --hf-file hermes2-gutenberg2-mistral-7b-q4_k_s.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Triangle104/Hermes2-Gutenberg2-Mistral-7B-Q4_K_S-GGUF --hf-file hermes2-gutenberg2-mistral-7b-q4_k_s.gguf -c 2048 ```