Instructions to use Q-bert/Merged-AGI-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Q-bert/Merged-AGI-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Q-bert/Merged-AGI-7B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Q-bert/Merged-AGI-7B") model = AutoModelForCausalLM.from_pretrained("Q-bert/Merged-AGI-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Q-bert/Merged-AGI-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Q-bert/Merged-AGI-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Q-bert/Merged-AGI-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Q-bert/Merged-AGI-7B
- SGLang
How to use Q-bert/Merged-AGI-7B 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 "Q-bert/Merged-AGI-7B" \ --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": "Q-bert/Merged-AGI-7B", "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 "Q-bert/Merged-AGI-7B" \ --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": "Q-bert/Merged-AGI-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Q-bert/Merged-AGI-7B with Docker Model Runner:
docker model run hf.co/Q-bert/Merged-AGI-7B
Commit History
-
Add base_models for merge (#3)
- Add base_models for merge (3f4ba77e6f9cd96c64257b93a58f7e288d62a788) Co-authored-by: Daniel van Strien <davanstrien@users.noreply.huggingface.co>264f92e
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add merge tag (#2)
- add merge tag (97e8dd9f2dc58ac91bade59927ab3eab09361d5a) Co-authored-by: Daniel van Strien <davanstrien@users.noreply.huggingface.co>d68a5bb
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Update README.md
cb0c68a -
Upload folder using huggingface_hub
7b81823 -
Update README.md
cad7f9f -
initial commit
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