Text Generation
Transformers
Safetensors
mixtral
Mixture of Experts
frankenmoe
Merge
mergekit
lazymergekit
yam-peleg/Experiment26-7B
mlabonne/AlphaMonarch-7B
text-generation-inference
Instructions to use jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2") model = AutoModelForCausalLM.from_pretrained("jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2
- SGLang
How to use jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2 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 "jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2" \ --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": "jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2", "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 "jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2" \ --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": "jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2 with Docker Model Runner:
docker model run hf.co/jsfs11/MixtureofMerges-MoE-2x7b-v6-8.0bpw-exl2
- Xet hash:
- 57712cbf36840e3524674dbd6b65bf0289084ddbe1ae2c99c6e77737bf0a0f0b
- Size of remote file:
- 1.68 GB
- SHA256:
- bd0e1d21c3b5f7b72885af2d33264e2f72709fc7b6b512849f179d30f921991f
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