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")# pip install -U transformers accelerate # 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
Download dolphin-2_2-yi-34b-Q5_0.gguf from second-state/Dolphin-2.2-Yi-34B-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 23.7 GB
-
https://huggingface.co/second-state/Dolphin-2.2-Yi-34B-GGUF/resolve/0003b013cac9ede7aa3f66258ea61793777b08f6/dolphin-2_2-yi-34b-Q5_0.gguf
- Command line
-
hf download hf://second-state/Dolphin-2.2-Yi-34B-GGUF@0003b013cac9ede7aa3f66258ea61793777b08f6/dolphin-2_2-yi-34b-Q5_0.gguf
-
curl -L -o dolphin-2_2-yi-34b-Q5_0.gguf https://huggingface.co/second-state/Dolphin-2.2-Yi-34B-GGUF/resolve/0003b013cac9ede7aa3f66258ea61793777b08f6/dolphin-2_2-yi-34b-Q5_0.gguf
23.7 GB
- Xet hash:
- c223f3d91897ee3de93d8fae9f0346a401040c1fb1a943577909bc594694490e
- Size of remote file:
- 23.7 GB
- SHA256:
- c99c11a7e2eff4b98c3d2f9f150131f8b94a02468c24e50ee68d57586962d1a0
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