Text Generation
Transformers
Safetensors
Arabic
English
jais
Arabic
English
LLM
Decoder
causal-lm
custom_code
8-bit precision
bitsandbytes
Instructions to use brainiac-origin/jais-chat-30b-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brainiac-origin/jais-chat-30b-8bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="brainiac-origin/jais-chat-30b-8bit", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("brainiac-origin/jais-chat-30b-8bit", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use brainiac-origin/jais-chat-30b-8bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "brainiac-origin/jais-chat-30b-8bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "brainiac-origin/jais-chat-30b-8bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/brainiac-origin/jais-chat-30b-8bit
- SGLang
How to use brainiac-origin/jais-chat-30b-8bit 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 "brainiac-origin/jais-chat-30b-8bit" \ --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": "brainiac-origin/jais-chat-30b-8bit", "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 "brainiac-origin/jais-chat-30b-8bit" \ --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": "brainiac-origin/jais-chat-30b-8bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use brainiac-origin/jais-chat-30b-8bit with Docker Model Runner:
docker model run hf.co/brainiac-origin/jais-chat-30b-8bit
Commit ·
b0f835d
1
Parent(s): b74ec8e
Upload tokenizer_config.json
Browse files- tokenizer_config.json +9 -0
tokenizer_config.json
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{
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"bos_token": "<|endoftext|>",
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|endoftext|>",
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"model_max_length": 2048,
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"pad_token": "<|endoftext|>",
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"tokenizer_class": "PreTrainedTokenizerFast",
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"unk_token": "<|endoftext|>"
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}
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