Text Generation
Transformers
ONNX
Safetensors
echo_hybrid
text-generation-inference
conversational
custom_code
Instructions to use mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2
- SGLang
How to use mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2 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 "mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2" \ --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": "mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2", "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 "mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2" \ --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": "mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2 with Docker Model Runner:
docker model run hf.co/mrs83/Kurtis-EON1-Hybrid-2B-v0.1.2
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[](https://huggingface.co/collections/ethicalabs/echo-dsrn-hybrid)
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[](https://github.com/ethicalabs-ai/Echo-DSRN/blob/main/PAPER.md)
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> * **No Production Deployment:** This model must not be deployed in commercial, enterprise, or mission-critical environments under any circumstances.
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> * **No Liability:** This model is provided "as-is" without warranties of any kind. The developers assume zero liability for downstream consequences, system integration failures, or regulatory non-compliance resulting from unauthorized deployment.
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## Model Details
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[](https://huggingface.co/collections/ethicalabs/echo-dsrn-hybrid)
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[](https://github.com/ethicalabs-ai/Echo-DSRN/blob/main/PAPER.md)
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> [!WARNING]
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> This repository contains experimental models designed strictly for academic evaluation and research purposes.
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> Critical Constraints:
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> * **No Production Deployment:** Experimental models must not be deployed in commercial, enterprise, or mission-critical environments under any circumstances.
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> * **No Liability:** Experimental models are provided "as-is" without warranties of any kind. The developers assume zero liability for downstream consequences, system integration failures, or regulatory non-compliance resulting from unauthorized deployment.
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## Model Details
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