Instructions to use berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher 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 berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0 # Run inference directly in the terminal: llama cli -hf berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0 # Run inference directly in the terminal: llama cli -hf berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher: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 berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher: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 berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0
Use Docker
docker model run hf.co/berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher with Ollama:
ollama run hf.co/berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher with Docker Model Runner:
docker model run hf.co/berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0
- Lemonade
How to use berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher:Q8_0
Run and chat with the model
lemonade run user.Qwen2.5-Coder-7B-Instruct-ifc2cypher-Q8_0
List all available models
lemonade list
- Atomic Chat
Download Modelfile from berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher: direct link, hf CLI and curl.
- Browser
- Download file 780 Bytes
-
https://huggingface.co/berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher/resolve/main/Modelfile
- Command line
-
hf download hf://berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher/Modelfile
-
curl -L -o Modelfile https://huggingface.co/berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher/resolve/main/Modelfile
780 Bytes
| FROM /content/berky12/Qwen2.5-Coder-7B-Instruct-ifc2cypher/unsloth.Q8_0.gguf | |
| TEMPLATE """{{ if .Prompt }}### Input: | |
| {{ .Prompt }} | |
| {{ end }}### Response: | |
| {{ .Response }} | |
| <|im_end|>""" | |
| PARAMETER stop "<|PAD_TOKEN|>" | |
| PARAMETER stop "<|quad_end|>" | |
| PARAMETER stop "<|box_end|>" | |
| PARAMETER stop "<|im_start|>" | |
| PARAMETER stop "<|file_sep|>" | |
| PARAMETER stop "<|image_pad|>" | |
| PARAMETER stop "<|object_ref_end|>" | |
| PARAMETER stop "<|repo_name|>" | |
| PARAMETER stop "<|video_pad|>" | |
| PARAMETER stop "<|endoftext|>" | |
| PARAMETER stop "<|quad_start|>" | |
| PARAMETER stop "</tool_call>" | |
| PARAMETER stop "<|box_start|>" | |
| PARAMETER stop "<|object_ref_start|>" | |
| PARAMETER stop "<tool_call>" | |
| PARAMETER stop "<|im_end|>" | |
| PARAMETER stop "<|fim_" | |
| PARAMETER stop "<|vision_" | |
| PARAMETER temperature 1.5 | |
| PARAMETER min_p 0.1 |