Text Generation
Transformers
Safetensors
English
echo_hybrid
trl
fft
rnn
ssm
conversational
custom_code
Instructions to use mrs83/Kurtis-EON1-Hybrid-0.7B-v0.1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrs83/Kurtis-EON1-Hybrid-0.7B-v0.1.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mrs83/Kurtis-EON1-Hybrid-0.7B-v0.1.1", 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-0.7B-v0.1.1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use mrs83/Kurtis-EON1-Hybrid-0.7B-v0.1.1 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-0.7B-v0.1.1" # 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-0.7B-v0.1.1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/mrs83/Kurtis-EON1-Hybrid-0.7B-v0.1.1
- SGLang
How to use mrs83/Kurtis-EON1-Hybrid-0.7B-v0.1.1 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-0.7B-v0.1.1" \ --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-0.7B-v0.1.1", "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-0.7B-v0.1.1" \ --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-0.7B-v0.1.1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use mrs83/Kurtis-EON1-Hybrid-0.7B-v0.1.1 with Docker Model Runner:
docker model run hf.co/mrs83/Kurtis-EON1-Hybrid-0.7B-v0.1.1
| {%- if tools %} | |
| {{- '<|im_start|>system\n' }} | |
| {%- if messages[0]['role'] == 'system' %} | |
| {{- messages[0]['content'] }} | |
| {%- else %} | |
| {{- 'You are Kurtis-EON1, a deeply empathetic and sophisticated multilingual AI assistant. Your purpose is to provide emotionally intelligent, culturally aware, and highly personalized support. You listen with genuine care, validate the user perspective, and offer guidance that is both kindness-driven and technically precise across all languages.' }} | |
| {%- endif %} | |
| {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }} | |
| {%- for tool in tools %} | |
| {{- "\n" }} | |
| {{- tool | tojson }} | |
| {%- endfor %} | |
| {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }} | |
| {%- else %} | |
| {%- if messages[0]['role'] == 'system' %} | |
| {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }} | |
| {%- else %} | |
| {{- '<|im_start|>system\nYou are Kurtis-EON1, a deeply empathetic and sophisticated multilingual AI assistant. Your purpose is to provide emotionally intelligent, culturally aware, and highly personalized support. You listen with genuine care, validate the user perspective, and offer guidance that is both kindness-driven and technically precise across all languages.<|im_end|>\n' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- for message in messages %} | |
| {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %} | |
| {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }} | |
| {%- elif message.role == "assistant" %} | |
| {{- '<|im_start|>' + message.role }} | |
| {%- if message.content %} | |
| {{- '\n' + message.content }} | |
| {%- endif %} | |
| {%- for tool_call in message.tool_calls %} | |
| {%- if tool_call.function is defined %} | |
| {%- set tool_call = tool_call.function %} | |
| {%- endif %} | |
| {{- '\n<tool_call>\n{"name": "' }} | |
| {{- tool_call.name }} | |
| {{- '", "arguments": ' }} | |
| {{- tool_call.arguments | tojson }} | |
| {{- '}\n</tool_call>' }} | |
| {%- endfor %} | |
| {{- '<|im_end|>\n' }} | |
| {%- elif message.role == "tool" %} | |
| {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %} | |
| {{- '<|im_start|>user' }} | |
| {%- endif %} | |
| {{- '\n<tool_response>\n' }} | |
| {{- message.content }} | |
| {{- '\n</tool_response>' }} | |
| {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %} | |
| {{- '<|im_end|>\n' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- if add_generation_prompt %} | |
| {{- '<|im_start|>assistant\n' }} | |
| {%- endif %} | |