Instructions to use sha-codes/qwen_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use sha-codes/qwen_ft with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf sha-codes/qwen_ft:Q4_K_M # Run inference directly in the terminal: llama cli -hf sha-codes/qwen_ft:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf sha-codes/qwen_ft:Q4_K_M # Run inference directly in the terminal: llama cli -hf sha-codes/qwen_ft: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 sha-codes/qwen_ft:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf sha-codes/qwen_ft: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 sha-codes/qwen_ft:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf sha-codes/qwen_ft:Q4_K_M
Use Docker
docker model run hf.co/sha-codes/qwen_ft:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use sha-codes/qwen_ft with Ollama:
ollama run hf.co/sha-codes/qwen_ft:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use sha-codes/qwen_ft with Docker Model Runner:
docker model run hf.co/sha-codes/qwen_ft:Q4_K_M
- Lemonade
How to use sha-codes/qwen_ft with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull sha-codes/qwen_ft:Q4_K_M
Run and chat with the model
lemonade run user.qwen_ft-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download Modelfile from sha-codes/qwen_ft: direct link, hf CLI and curl.
- Browser
- Download file 834 Bytes
-
https://huggingface.co/sha-codes/qwen_ft/resolve/main/Modelfile
- Command line
-
hf download hf://sha-codes/qwen_ft/Modelfile
-
curl -L -o Modelfile https://huggingface.co/sha-codes/qwen_ft/resolve/main/Modelfile
834 Bytes
| FROM /content/sha-codes/qwen_ft/unsloth.F16.gguf | |
| TEMPLATE """Below are instructions that describe some tasks. Write responses that appropriately complete each request.{{ if .Prompt }} | |
| ### Instruction: | |
| {{ .Prompt }}{{ end }} | |
| ### Response: | |
| {{ .Response }}<|im_end|>""" | |
| PARAMETER stop "<|box_start|>" | |
| PARAMETER stop "<|endoftext|>" | |
| PARAMETER stop "<|quad_end|>" | |
| PARAMETER stop "<tool_call>" | |
| PARAMETER stop "<|file_sep|>" | |
| PARAMETER stop "<|box_end|>" | |
| PARAMETER stop "<|repo_name|>" | |
| PARAMETER stop "<|image_pad|>" | |
| PARAMETER stop "<|video_pad|>" | |
| PARAMETER stop "<|quad_start|>" | |
| PARAMETER stop "<|object_ref_start|>" | |
| PARAMETER stop "</tool_call>" | |
| PARAMETER stop "<|object_ref_end|>" | |
| PARAMETER stop "<|im_start|>" | |
| PARAMETER stop "<|im_end|>" | |
| PARAMETER stop "<|vision_" | |
| PARAMETER stop "<|fim_" | |
| PARAMETER temperature 1.5 | |
| PARAMETER min_p 0.1 |