Instructions to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", trust_remote_code=True, dtype="auto") - Mobilint
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="HyperCLOVAX-SEED-Text-Instruct-1.5B", model_type="DEFAULT", model_path="", core_mode="global8", ) try: image = model.preprocess("path/to/image.jpg") output = model(image) result = model.postprocess(output) finally: model.dispose() - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B
- SGLang
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B 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 "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B with Docker Model Runner:
docker model run hf.co/mobilint/HyperCLOVAX-SEED-Text-Instruct-1.5B
Create proxy_llama.py
Browse files- proxy_llama.py +14 -0
proxy_llama.py
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try:
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from mblt_model_zoo.hf_transformers.models.llama.configuration_llama import (
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MobilintLlamaConfig,
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)
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from mblt_model_zoo.hf_transformers.models.llama.modeling_llama import (
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MobilintLlamaForCausalLM,
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)
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except ImportError:
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raise ImportError(
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"This model requires 'mblt_model_zoo' to be installed. "
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"Please run: pip install mblt_model_zoo[transformers]"
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)
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__all__ = ["MobilintLlamaConfig", "MobilintLlamaForCausalLM"]
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