Text Generation
Transformers
Safetensors
granite_switch
language
granite-switch
granite-4.1
conversational
Instructions to use ibm-granite/granite-switch-4.1-3b-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-granite/granite-switch-4.1-3b-preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ibm-granite/granite-switch-4.1-3b-preview") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ibm-granite/granite-switch-4.1-3b-preview", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ibm-granite/granite-switch-4.1-3b-preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ibm-granite/granite-switch-4.1-3b-preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ibm-granite/granite-switch-4.1-3b-preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ibm-granite/granite-switch-4.1-3b-preview
- SGLang
How to use ibm-granite/granite-switch-4.1-3b-preview 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 "ibm-granite/granite-switch-4.1-3b-preview" \ --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": "ibm-granite/granite-switch-4.1-3b-preview", "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 "ibm-granite/granite-switch-4.1-3b-preview" \ --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": "ibm-granite/granite-switch-4.1-3b-preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ibm-granite/granite-switch-4.1-3b-preview with Docker Model Runner:
docker model run hf.co/ibm-granite/granite-switch-4.1-3b-preview
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|end_of_text|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|end_of_text|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|citations|>", | |
| "<|query_rewrite|>", | |
| "<|query_clarification|>", | |
| "<|hallucination_detection|>", | |
| "<|answerability|>", | |
| "<|factuality-detection|>", | |
| "<|policy-guardrails|>", | |
| "<|factuality-correction|>", | |
| "<|guardian-core|>", | |
| "<|uncertainty|>", | |
| "<|requirement-check|>", | |
| "<|context-attribution|>" | |
| ], | |
| "is_local": true, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|pad|>", | |
| "padding_side": "left", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|unk|>" | |
| } | |