Text Generation
Transformers
Safetensors
Arabic
llama
arabic
arabic-language-model
causal-lm
egyptian-arabic
arabic-dialects
base-model
slm
horus
tokenai
text-generation-inference
Instructions to use tokenaii/Horus-Taleeq-0.2B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tokenaii/Horus-Taleeq-0.2B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tokenaii/Horus-Taleeq-0.2B-Base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tokenaii/Horus-Taleeq-0.2B-Base") model = AutoModelForCausalLM.from_pretrained("tokenaii/Horus-Taleeq-0.2B-Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tokenaii/Horus-Taleeq-0.2B-Base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tokenaii/Horus-Taleeq-0.2B-Base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tokenaii/Horus-Taleeq-0.2B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tokenaii/Horus-Taleeq-0.2B-Base
- SGLang
How to use tokenaii/Horus-Taleeq-0.2B-Base with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "tokenaii/Horus-Taleeq-0.2B-Base" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tokenaii/Horus-Taleeq-0.2B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "tokenaii/Horus-Taleeq-0.2B-Base" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tokenaii/Horus-Taleeq-0.2B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tokenaii/Horus-Taleeq-0.2B-Base with Docker Model Runner:
docker model run hf.co/tokenaii/Horus-Taleeq-0.2B-Base
docs: cross-link GitHub and describe TokenAI
Browse files
README.md
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# Horus Taleeq 0.2 Base
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Horus Taleeq 0.2 Base is an **Arabic-only Small Language Model (SLM)** with a
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decoder-only causal Transformer architecture, developed by TokenAI.
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chat release.
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## Ownership and development
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- Lead developer: **Assem Sabry**
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- Hugging Face organization: [tokenaii](https://huggingface.co/tokenaii)
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- Model repository: [tokenaii/Horus-Taleeq-0.2-base](https://huggingface.co/tokenaii/Horus-Taleeq-0.2-base)
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## Model summary
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# Horus Taleeq 0.2 Base
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Horus Taleeq 0.2 Base is an **Arabic-only Small Language Model (SLM)** with a
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decoder-only causal Transformer architecture, developed by TokenAI. TokenAI is a startup and nonprofit organization
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focused on open Arabic AI research and model development. It is a ready-to-build-on
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base checkpoint, not a finished instruction-tuned or production chat release.
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## Ownership and development
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- Lead developer: **Assem Sabry**
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- Hugging Face organization: [tokenaii](https://huggingface.co/tokenaii)
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- Model repository: [tokenaii/Horus-Taleeq-0.2-base](https://huggingface.co/tokenaii/Horus-Taleeq-0.2-base)
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- GitHub repository: [tokenaii/Horus-Taleeq-0.2B](https://github.com/tokenaii/Horus-Taleeq-0.2B)
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## Model summary
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