Instructions to use digitalai/DgMind-20B-Adapters with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use digitalai/DgMind-20B-Adapters with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gpt-oss-20b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "digitalai/DgMind-20B-Adapters") - Transformers
How to use digitalai/DgMind-20B-Adapters with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="digitalai/DgMind-20B-Adapters") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("digitalai/DgMind-20B-Adapters", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use digitalai/DgMind-20B-Adapters 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 digitalai/DgMind-20B-Adapters:MXFP4 # Run inference directly in the terminal: llama cli -hf digitalai/DgMind-20B-Adapters:MXFP4
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf digitalai/DgMind-20B-Adapters:MXFP4 # Run inference directly in the terminal: llama cli -hf digitalai/DgMind-20B-Adapters:MXFP4
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf digitalai/DgMind-20B-Adapters:MXFP4 # Run inference directly in the terminal: ./build/bin/llama cli -hf digitalai/DgMind-20B-Adapters:MXFP4
Use Docker
docker model run hf.co/digitalai/DgMind-20B-Adapters:MXFP4
- Llama new
- LM Studio
- Jan
- vLLM
How to use digitalai/DgMind-20B-Adapters with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "digitalai/DgMind-20B-Adapters" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "digitalai/DgMind-20B-Adapters", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/digitalai/DgMind-20B-Adapters:MXFP4
- SGLang
How to use digitalai/DgMind-20B-Adapters 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 "digitalai/DgMind-20B-Adapters" \ --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": "digitalai/DgMind-20B-Adapters", "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 "digitalai/DgMind-20B-Adapters" \ --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": "digitalai/DgMind-20B-Adapters", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use digitalai/DgMind-20B-Adapters with Ollama:
ollama run hf.co/digitalai/DgMind-20B-Adapters:MXFP4
- Unsloth Desktop
- Docker Model Runner
How to use digitalai/DgMind-20B-Adapters with Docker Model Runner:
docker model run hf.co/digitalai/DgMind-20B-Adapters:MXFP4
- Lemonade
How to use digitalai/DgMind-20B-Adapters with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull digitalai/DgMind-20B-Adapters:MXFP4
Run and chat with the model
lemonade run user.DgMind-20B-Adapters-MXFP4
List all available models
lemonade list
- Atomic Chat
Download tokenizer.json from digitalai/DgMind-20B-Adapters: direct link, hf CLI and curl.
- Browser
- Download file 27.9 MB
-
https://huggingface.co/digitalai/DgMind-20B-Adapters/resolve/main/tokenizer.json
- Command line
-
hf download hf://digitalai/DgMind-20B-Adapters/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/digitalai/DgMind-20B-Adapters/resolve/main/tokenizer.json
27.9 MB
- Xet hash:
- 59f22360b51bf1a137fb80e14df310b4b249bed6cc64565aa0c401ca19ffcd04
- Size of remote file:
- 27.9 MB
- SHA256:
- 0614fe83cadab421296e664e1f48f4261fa8fef6e03e63bb75c20f38e37d07d3
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