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https://colab.research.google.com/drive/1c7oHSEemh8Ih4ExRd4bQ6WHADVY-Mfj1#scrollTo=ADmdVbV93wpy
- base_model: silma-ai/SILMA-9B-Instruct-v1.0 language:
- ar
- en library_name: transformers license: gemma pipeline_tag: text-generation tags:
- conversational
- llama-cpp
- gguf-my-repo extra_gated_button_content: Acknowledge license model-index:
- name: SILMA-9B-Instruct-v1.0
results:
- task:
type: text-generation
dataset:
name: MMLU (Arabic)
type: OALL/Arabic_MMLU
metrics:
- type: loglikelihood_acc_norm value: 52.55 name: acc_norm source: url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard name: Open Arabic LLM Leaderboard
- task:
type: text-generation
dataset:
name: AlGhafa
type: OALL/AlGhafa-Arabic-LLM-Benchmark-Native
metrics:
- type: loglikelihood_acc_norm value: 71.85 name: acc_norm source: url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard name: Open Arabic LLM Leaderboard
- task:
type: text-generation
dataset:
name: ARC Challenge (Arabic)
type: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated
metrics:
- type: loglikelihood_acc_norm value: 78.19 name: acc_norm
- type: loglikelihood_acc_norm value: 86 name: acc_norm
- type: loglikelihood_acc_norm value: 64.05 name: acc_norm
- type: loglikelihood_acc_norm value: 78.89 name: acc_norm
- type: loglikelihood_acc_norm value: 47.64 name: acc_norm
- type: loglikelihood_acc_norm value: 72.93 name: acc_norm
- type: loglikelihood_acc_norm value: 71.96 name: acc_norm
- type: loglikelihood_acc_norm value: 75.55 name: acc_norm
- type: loglikelihood_acc_norm value: 91.26 name: acc_norm
- type: loglikelihood_acc_norm value: 67.59 name: acc_norm source: url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard name: Open Arabic LLM Leaderboard
- task:
type: text-generation
dataset:
name: ACVA
type: OALL/ACVA
metrics:
- type: loglikelihood_acc_norm value: 78.89 name: acc_norm source: url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard name: Open Arabic LLM Leaderboard
- task:
type: text-generation
dataset:
name: Arabic_EXAMS
type: OALL/Arabic_EXAMS
metrics:
- type: loglikelihood_acc_norm value: 51.4 name: acc_norm source: url: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard name: Open Arabic LLM Leaderboard
- task:
type: text-generation
dataset:
name: MMLU (Arabic)
type: OALL/Arabic_MMLU
metrics:
goodasdgood/SILMA-9B-Instruct-v1.0-IQ4_NL-GGUF
This model was converted to GGUF format from silma-ai/SILMA-9B-Instruct-v1.0
using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
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"
Server:
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
Note: You can also use this checkpoint directly through the usage steps 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 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"
or
./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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