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")# 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
- Xet hash:
- 12f289180164eb656628ffff209eaf67508d55a55d033807d7a17c445e845943
- Size of remote file:
- 2.95 MB
- SHA256:
- 116147d034e7935a54e6a438fa078b390b0726eab14eb40829e3270c5b6f6fd4
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