Instructions to use QCRI/Fanar-1-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QCRI/Fanar-1-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="QCRI/Fanar-1-9B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("QCRI/Fanar-1-9B") model = AutoModelForCausalLM.from_pretrained("QCRI/Fanar-1-9B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use QCRI/Fanar-1-9B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "QCRI/Fanar-1-9B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QCRI/Fanar-1-9B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/QCRI/Fanar-1-9B
- SGLang
How to use QCRI/Fanar-1-9B 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 "QCRI/Fanar-1-9B" \ --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": "QCRI/Fanar-1-9B", "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 "QCRI/Fanar-1-9B" \ --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": "QCRI/Fanar-1-9B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use QCRI/Fanar-1-9B with Docker Model Runner:
docker model run hf.co/QCRI/Fanar-1-9B
Update model_max_length in tokenizer config to 4096
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
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@@ -1998,7 +1998,7 @@
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| 1998 |
"bos_token": "<bos>",
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| 1999 |
"clean_up_tokenization_spaces": false,
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"eos_token": "<eos>",
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-
"model_max_length":
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| 2002 |
"pad_token": "<pad>",
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"sp_model_kwargs": {},
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| 2004 |
"spaces_between_special_tokens": false,
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| 1998 |
"bos_token": "<bos>",
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| 1999 |
"clean_up_tokenization_spaces": false,
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| 2000 |
"eos_token": "<eos>",
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| 2001 |
+
"model_max_length": 4096,
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| 2002 |
"pad_token": "<pad>",
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| 2003 |
"sp_model_kwargs": {},
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| 2004 |
"spaces_between_special_tokens": false,
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