Instructions to use stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat", dtype="auto")

llama-cpp-python

How to use stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat",
	filename="Qwen2.5-Coder-7B-Instruct-codegate-fim-chat-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M

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 stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M

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 stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M

Use Docker

docker model run hf.co/stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M

LM Studio
Jan
Ollama
How to use stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat with Ollama:
```
ollama run hf.co/stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M
```

Unsloth Studio new

How to use stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat 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 stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat 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 stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat to start chatting

Pi new

How to use stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M

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": "Qwen2.5-Coder-7B-Instruct-codegate-fim-chat"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat with Docker Model Runner:
```
docker model run hf.co/stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M
```

Lemonade

How to use stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat:Q4_K_M

Run and chat with the model

lemonade run user.Qwen2.5-Coder-7B-Instruct-codegate-fim-chat-Q4_K_M

List all available models

lemonade list

Qwen2.5-Coder-7B-Instruct-codegate-fim-chat

File size: 1,718 Bytes


FROM /home/ptelang/research/modelfinetuning/stacklok/Qwen2.5-Coder-7B-Instruct-codegate-fim-chat/unsloth.BF16.gguf
TEMPLATE """{{- if .Messages }}
{{- if or .System .Tools }}<|im_start|>system
{{- if .System }}
{{ .System }}
{{- end }}
{{- if .Tools }}

# Tools

You may call one or more functions to assist with the user query.

You are provided with function signatures within <tools></tools> XML tags:
<tools>
{{- range .Tools }}
{"type": "function", "function": {{ .Function }}}
{{- end }}
</tools>

For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
<tool_call>
{"name": <function-name>, "arguments": <args-json-object>}
</tool_call>
{{- end }}<|im_end|>
{{ end }}
{{- range $i, $_ := .Messages }}
{{- $last := eq (len (slice $.Messages $i)) 1 -}}
{{- if eq .Role "user" }}<|im_start|>user
{{ .Content }}<|im_end|>
{{ else if eq .Role "assistant" }}<|im_start|>assistant
{{ if .Content }}{{ .Content }}
{{- else if .ToolCalls }}<tool_call>
{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
{{ end }}</tool_call>
{{- end }}{{ if not $last }}<|im_end|>
{{ end }}
{{- else if eq .Role "tool" }}<|im_start|>user
<tool_response>
{{ .Content }}
</tool_response><|im_end|>
{{ end }}
{{- if and (ne .Role "assistant") $last }}<|im_start|>assistant
{{ end }}
{{- end }}
{{- else }}
{{- if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}"""
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|endoftext|>"
PARAMETER temperature 1.5
PARAMETER min_p 0.1