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+ ---
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+ base_model: mlabonne/NeuralHermes-2.5-Mistral-7B-laser
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+ datasets:
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+ - mlabonne/chatml_dpo_pairs
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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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+ - 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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+ - distillation
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+ - dpo
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+ - rlhf
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+ - laser
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+ - llama-cpp
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+ - gguf-my-repo
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+ model-index:
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+ - name: NeuralHermes-2.5-Mistral-7B-laser
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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: 66.38
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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=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
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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: 85.09
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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=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
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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: 63.43
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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=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
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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: 54.95
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
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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: 78.14
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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=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
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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: 55.72
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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=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
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+ name: Open LLM Leaderboard
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+ ---
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+
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+ # Bakanayatsu/NeuralHermes-2.5-Mistral-7B-laser-Q4_K_S-GGUF
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+ This model was converted to GGUF format from [`mlabonne/NeuralHermes-2.5-Mistral-7B-laser`](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B-laser) 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/mlabonne/NeuralHermes-2.5-Mistral-7B-laser) for more details on the model.
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+
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+ ## Use with llama.cpp
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+ Install llama.cpp through brew (works on Mac and Linux)
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+
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+ ```bash
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+ brew install llama.cpp
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+
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+ ```
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+ Invoke the llama.cpp server or the CLI.
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+
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+ ### CLI:
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+ ```bash
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+ llama-cli --hf-repo Bakanayatsu/NeuralHermes-2.5-Mistral-7B-laser-Q4_K_S-GGUF --hf-file neuralhermes-2.5-mistral-7b-laser-q4_k_s-imat.gguf -p "The meaning to life and the universe is"
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+ ```
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+
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+ ### Server:
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+ ```bash
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+ llama-server --hf-repo Bakanayatsu/NeuralHermes-2.5-Mistral-7B-laser-Q4_K_S-GGUF --hf-file neuralhermes-2.5-mistral-7b-laser-q4_k_s-imat.gguf -c 2048
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+ ```
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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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+ Step 1: Clone llama.cpp from GitHub.
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+ ```
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+ git clone https://github.com/ggerganov/llama.cpp
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+ ```
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+
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+ 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).
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+ ```
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+ cd llama.cpp && LLAMA_CURL=1 make
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+ ```
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+
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+ Step 3: Run inference through the main binary.
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+ ```
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+ ./llama-cli --hf-repo Bakanayatsu/NeuralHermes-2.5-Mistral-7B-laser-Q4_K_S-GGUF --hf-file neuralhermes-2.5-mistral-7b-laser-q4_k_s-imat.gguf -p "The meaning to life and the universe is"
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+ ```
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+ or
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+ ```
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+ ./llama-server --hf-repo Bakanayatsu/NeuralHermes-2.5-Mistral-7B-laser-Q4_K_S-GGUF --hf-file neuralhermes-2.5-mistral-7b-laser-q4_k_s-imat.gguf -c 2048
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+ ```