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--- |
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base_model: HuggingFaceH4/zephyr-7b-beta |
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datasets: |
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- HuggingFaceH4/ultrachat_200k |
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- HuggingFaceH4/ultrafeedback_binarized |
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language: |
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- en |
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license: mit |
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pipeline_tag: text-generation |
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tags: |
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- generated_from_trainer |
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- llama-cpp |
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- gguf-my-repo |
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widget: |
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- example_title: Pirate! |
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messages: |
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- role: system |
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content: You are a pirate chatbot who always responds with Arr! |
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- role: user |
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content: There's a llama on my lawn, how can I get rid of him? |
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output: |
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text: Arr! 'Tis a puzzlin' matter, me hearty! A llama on yer lawn be a rare sight, |
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but I've got a plan that might help ye get rid of 'im. Ye'll need to gather |
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some carrots and hay, and then lure the llama away with the promise of a tasty |
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treat. Once he's gone, ye can clean up yer lawn and enjoy the peace and quiet |
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once again. But beware, me hearty, for there may be more llamas where that one |
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came from! Arr! |
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model-index: |
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- name: zephyr-7b-beta |
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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: 62.03071672354948 |
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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=HuggingFaceH4/zephyr-7b-beta |
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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: 84.35570603465445 |
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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=HuggingFaceH4/zephyr-7b-beta |
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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: Drop (3-Shot) |
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type: drop |
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split: validation |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: f1 |
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value: 9.66243708053691 |
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name: f1 score |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta |
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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: 57.44916942762855 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta |
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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: 12.736921910538287 |
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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=HuggingFaceH4/zephyr-7b-beta |
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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: 61.07 |
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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=HuggingFaceH4/zephyr-7b-beta |
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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: 77.7426992896606 |
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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=HuggingFaceH4/zephyr-7b-beta |
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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: AlpacaEval |
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type: tatsu-lab/alpaca_eval |
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metrics: |
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- type: unknown |
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value: 0.906 |
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name: win rate |
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source: |
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url: https://tatsu-lab.github.io/alpaca_eval/ |
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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: MT-Bench |
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type: unknown |
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metrics: |
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- type: unknown |
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value: 7.34 |
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name: score |
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source: |
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url: https://huggingface.co/spaces/lmsys/mt-bench |
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--- |
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|
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# peterpeter8585/zephyr-7b-beta-Q4_K_M-GGUF |
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This model was converted to GGUF format from [`HuggingFaceH4/zephyr-7b-beta`](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) 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/HuggingFaceH4/zephyr-7b-beta) 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 peterpeter8585/zephyr-7b-beta-Q4_K_M-GGUF --hf-file zephyr-7b-beta-q4_k_m.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 peterpeter8585/zephyr-7b-beta-Q4_K_M-GGUF --hf-file zephyr-7b-beta-q4_k_m.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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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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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo peterpeter8585/zephyr-7b-beta-Q4_K_M-GGUF --hf-file zephyr-7b-beta-q4_k_m.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 peterpeter8585/zephyr-7b-beta-Q4_K_M-GGUF --hf-file zephyr-7b-beta-q4_k_m.gguf -c 2048 |
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``` |
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