Instructions to use second-state/Dolphin-2.2-Yi-34B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use second-state/Dolphin-2.2-Yi-34B-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="second-state/Dolphin-2.2-Yi-34B-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("second-state/Dolphin-2.2-Yi-34B-GGUF") model = AutoModelForCausalLM.from_pretrained("second-state/Dolphin-2.2-Yi-34B-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use second-state/Dolphin-2.2-Yi-34B-GGUF 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 second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf second-state/Dolphin-2.2-Yi-34B-GGUF: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 second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf second-state/Dolphin-2.2-Yi-34B-GGUF: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 second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use second-state/Dolphin-2.2-Yi-34B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "second-state/Dolphin-2.2-Yi-34B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "second-state/Dolphin-2.2-Yi-34B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M
- SGLang
How to use second-state/Dolphin-2.2-Yi-34B-GGUF 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 "second-state/Dolphin-2.2-Yi-34B-GGUF" \ --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": "second-state/Dolphin-2.2-Yi-34B-GGUF", "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 "second-state/Dolphin-2.2-Yi-34B-GGUF" \ --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": "second-state/Dolphin-2.2-Yi-34B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use second-state/Dolphin-2.2-Yi-34B-GGUF with Ollama:
ollama run hf.co/second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use second-state/Dolphin-2.2-Yi-34B-GGUF with Docker Model Runner:
docker model run hf.co/second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M
- Lemonade
How to use second-state/Dolphin-2.2-Yi-34B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull second-state/Dolphin-2.2-Yi-34B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Dolphin-2.2-Yi-34B-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Update README.md with license information
Hi, I'm Chen, a DevRel specialist from 01.AI.
Today I'm sending you the PR to help you update the model license, and give a recommendation according to apache-2.0.
1. License Update:
Since license of all Yi Series models has been updated from yi-license to apache-2.0, this PR is to help you update it.
License under apache-2.0 enables more free and flexible use and distribution, promoting open collaboration and innovation.
It can be a good choice to make your models widely available and provide access which is reliable and high-quality. (https://www.apache.org/licenses/LICENSE-2.0)
If it looks good to you, you can choose to update other yi derivatives (if you have) license to apache-2.0 on your own if I miss out.
2. Recommendation for Yi Derivatives:
All Yi Series models are now licensed under apache-2.0. It is recomended that Yi derivatives mention the specific Yi models they're based on in any place (e.g., in the Model Card) to align with the requirement of apache-2.0.
Thanks for your continued support and contributions to Yi models.
Thanks for this update!