Text Generation
Transformers
Safetensors
GGUF
English
code
code-editing
Merge
fastedit
qwen2
conversational
Instructions to use continuous-lab/FastEdit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use continuous-lab/FastEdit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="continuous-lab/FastEdit") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("continuous-lab/FastEdit", dtype="auto") - llama-cpp-python
How to use continuous-lab/FastEdit with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="continuous-lab/FastEdit", filename="gguf/fastedit-1.7b-Q8_0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use continuous-lab/FastEdit with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf continuous-lab/FastEdit:Q8_0 # Run inference directly in the terminal: llama-cli -hf continuous-lab/FastEdit:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf continuous-lab/FastEdit:Q8_0 # Run inference directly in the terminal: llama-cli -hf continuous-lab/FastEdit:Q8_0
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf continuous-lab/FastEdit:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf continuous-lab/FastEdit:Q8_0
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf continuous-lab/FastEdit:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf continuous-lab/FastEdit:Q8_0
Use Docker
docker model run hf.co/continuous-lab/FastEdit:Q8_0
- LM Studio
- Jan
- vLLM
How to use continuous-lab/FastEdit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "continuous-lab/FastEdit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "continuous-lab/FastEdit", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/continuous-lab/FastEdit:Q8_0
- SGLang
How to use continuous-lab/FastEdit 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 "continuous-lab/FastEdit" \ --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": "continuous-lab/FastEdit", "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 "continuous-lab/FastEdit" \ --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": "continuous-lab/FastEdit", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use continuous-lab/FastEdit with Ollama:
ollama run hf.co/continuous-lab/FastEdit:Q8_0
- Unsloth Studio
How to use continuous-lab/FastEdit with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for continuous-lab/FastEdit to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for continuous-lab/FastEdit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for continuous-lab/FastEdit to start chatting
- Pi
How to use continuous-lab/FastEdit with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf continuous-lab/FastEdit:Q8_0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "continuous-lab/FastEdit:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use continuous-lab/FastEdit with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf continuous-lab/FastEdit:Q8_0
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default continuous-lab/FastEdit:Q8_0
Run Hermes
hermes
- Docker Model Runner
How to use continuous-lab/FastEdit with Docker Model Runner:
docker model run hf.co/continuous-lab/FastEdit:Q8_0
- Lemonade
How to use continuous-lab/FastEdit with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull continuous-lab/FastEdit:Q8_0
Run and chat with the model
lemonade run user.FastEdit-Q8_0
List all available models
lemonade list
| {%- if tools %} | |
| {{- '<|im_start|>system\n' }} | |
| {%- if messages[0].role == 'system' %} | |
| {{- messages[0].content + '\n\n' }} | |
| {%- endif %} | |
| {{- "# 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' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} | |
| {%- for forward_message in messages %} | |
| {%- set index = (messages|length - 1) - loop.index0 %} | |
| {%- set message = messages[index] %} | |
| {%- set tool_start = '<tool_response>' %} | |
| {%- set tool_start_length = tool_start|length %} | |
| {%- set start_of_message = message.content[:tool_start_length] %} | |
| {%- set tool_end = '</tool_response>' %} | |
| {%- set tool_end_length = tool_end|length %} | |
| {%- set start_pos = (message.content|length) - tool_end_length %} | |
| {%- if start_pos < 0 %} | |
| {%- set start_pos = 0 %} | |
| {%- endif %} | |
| {%- set end_of_message = message.content[start_pos:] %} | |
| {%- if ns.multi_step_tool and message.role == "user" and not(start_of_message == tool_start and end_of_message == tool_end) %} | |
| {%- set ns.multi_step_tool = false %} | |
| {%- set ns.last_query_index = index %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- for message in messages %} | |
| {%- if (message.role == "user") or (message.role == "system" and not loop.first) %} | |
| {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }} | |
| {%- elif message.role == "assistant" %} | |
| {%- set content = message.content %} | |
| {%- set reasoning_content = '' %} | |
| {%- if message.reasoning_content is defined and message.reasoning_content is not none %} | |
| {%- set reasoning_content = message.reasoning_content %} | |
| {%- else %} | |
| {%- if '</think>' in message.content %} | |
| {%- set content = (message.content.split('</think>')|last).lstrip('\n') %} | |
| {%- set reasoning_content = (message.content.split('</think>')|first).rstrip('\n') %} | |
| {%- set reasoning_content = (reasoning_content.split('<think>')|last).lstrip('\n') %} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- if loop.index0 > ns.last_query_index %} | |
| {%- if loop.last or (not loop.last and reasoning_content) %} | |
| {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }} | |
| {%- else %} | |
| {{- '<|im_start|>' + message.role + '\n' + content }} | |
| {%- endif %} | |
| {%- else %} | |
| {{- '<|im_start|>' + message.role + '\n' + content }} | |
| {%- endif %} | |
| {%- if message.tool_calls %} | |
| {%- for tool_call in message.tool_calls %} | |
| {%- if (loop.first and content) or (not loop.first) %} | |
| {{- '\n' }} | |
| {%- endif %} | |
| {%- if tool_call.function %} | |
| {%- set tool_call = tool_call.function %} | |
| {%- endif %} | |
| {{- '<tool_call>\n{"name": "' }} | |
| {{- tool_call.name }} | |
| {{- '", "arguments": ' }} | |
| {%- if tool_call.arguments is string %} | |
| {{- tool_call.arguments }} | |
| {%- else %} | |
| {{- tool_call.arguments | tojson }} | |
| {%- endif %} | |
| {{- '}\n</tool_call>' }} | |
| {%- endfor %} | |
| {%- endif %} | |
| {{- '<|im_end|>\n' }} | |
| {%- elif message.role == "tool" %} | |
| {%- if loop.first 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' }} | |
| {%- if enable_thinking is defined and enable_thinking is true %} | |
| {{- '<think>\n' }} | |
| {%- else %} | |
| {{- '<think>\n\n</think>\n\n' }} | |
| {%- endif %} | |
| {%- endif %} |