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Update README.md
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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
---
# goodasdgood/SILMA-9B-Instruct-v1.0-IQ4_NL-GGUF
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.
Refer to the [original model card](https://huggingface.co/silma-ai/SILMA-9B-Instruct-v1.0) for more details on the model.
## 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 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:
```bash
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](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 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
```