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README.md
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---
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base_model: silma-ai/SILMA-9B-Instruct-v1.0
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language:
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- ar
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- en
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library_name: transformers
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license: gemma
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pipeline_tag: text-generation
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tags:
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- conversational
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- llama-cpp
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- gguf-my-repo
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extra_gated_button_content: Acknowledge license
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model-index:
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- name: SILMA-9B-Instruct-v1.0
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results:
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- task:
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type: text-generation
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dataset:
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name: MMLU (Arabic)
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type: OALL/Arabic_MMLU
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metrics:
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- type: loglikelihood_acc_norm
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value: 52.55
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard
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name: Open Arabic LLM Leaderboard
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- task:
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type: text-generation
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dataset:
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name: AlGhafa
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type: OALL/AlGhafa-Arabic-LLM-Benchmark-Native
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metrics:
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- type: loglikelihood_acc_norm
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value: 71.85
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard
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name: Open Arabic LLM Leaderboard
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- task:
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type: text-generation
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dataset:
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name: ARC Challenge (Arabic)
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type: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated
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metrics:
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- type: loglikelihood_acc_norm
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value: 78.19
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name: acc_norm
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- type: loglikelihood_acc_norm
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value: 86
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name: acc_norm
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- type: loglikelihood_acc_norm
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value: 64.05
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name: acc_norm
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- type: loglikelihood_acc_norm
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value: 78.89
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name: acc_norm
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- type: loglikelihood_acc_norm
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value: 47.64
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name: acc_norm
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- type: loglikelihood_acc_norm
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value: 72.93
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name: acc_norm
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- type: loglikelihood_acc_norm
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value: 71.96
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name: acc_norm
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- type: loglikelihood_acc_norm
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value: 75.55
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name: acc_norm
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- type: loglikelihood_acc_norm
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value: 91.26
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name: acc_norm
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- type: loglikelihood_acc_norm
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value: 67.59
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard
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name: Open Arabic LLM Leaderboard
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- task:
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type: text-generation
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dataset:
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name: ACVA
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type: OALL/ACVA
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metrics:
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- type: loglikelihood_acc_norm
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value: 78.89
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard
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name: Open Arabic LLM Leaderboard
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- task:
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type: text-generation
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dataset:
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name: Arabic_EXAMS
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type: OALL/Arabic_EXAMS
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metrics:
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- type: loglikelihood_acc_norm
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value: 51.4
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard
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name: Open Arabic LLM Leaderboard
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---
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# goodasdgood/SILMA-9B-Instruct-v1.0-IQ4_NL-GGUF
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This model was converted to GGUF format from [`silma-ai/SILMA-9B-Instruct-v1.0`](https://huggingface.co/silma-ai/SILMA-9B-Instruct-v1.0) 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/silma-ai/SILMA-9B-Instruct-v1.0) for more details on the model.
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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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```bash
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brew install 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 goodasdgood/SILMA-9B-Instruct-v1.0-IQ4_NL-GGUF --hf-file silma-9b-instruct-v1.0-iq4_nl-imat.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 goodasdgood/SILMA-9B-Instruct-v1.0-IQ4_NL-GGUF --hf-file silma-9b-instruct-v1.0-iq4_nl-imat.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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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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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 goodasdgood/SILMA-9B-Instruct-v1.0-IQ4_NL-GGUF --hf-file silma-9b-instruct-v1.0-iq4_nl-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 goodasdgood/SILMA-9B-Instruct-v1.0-IQ4_NL-GGUF --hf-file silma-9b-instruct-v1.0-iq4_nl-imat.gguf -c 2048
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```
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