Text Generation
Transformers
Safetensors
granite
granite-4.2
reasoning
thinking
tool-calling
ibm
conversational
Instructions to use ibm-granite/granite-4.2-30b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-granite/granite-4.2-30b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ibm-granite/granite-4.2-30b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ibm-granite/granite-4.2-30b") model = AutoModelForCausalLM.from_pretrained("ibm-granite/granite-4.2-30b", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- HuggingChat
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ibm-granite/granite-4.2-30b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ibm-granite/granite-4.2-30b" # 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-4.2-30b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ibm-granite/granite-4.2-30b
- SGLang
How to use ibm-granite/granite-4.2-30b 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-4.2-30b" \ --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-4.2-30b", "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-4.2-30b" \ --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-4.2-30b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ibm-granite/granite-4.2-30b with Docker Model Runner:
docker model run hf.co/ibm-granite/granite-4.2-30b
Update chat_template.jinja
Browse files- chat_template.jinja +3 -0
chat_template.jinja
CHANGED
|
@@ -12,6 +12,9 @@
|
|
| 12 |
{%- endmacro -%}
|
| 13 |
{%- set enable_thinking = enable_thinking if enable_thinking is defined else True %}
|
| 14 |
{%- set low_effort = low_effort if low_effort is defined else False %}
|
|
|
|
|
|
|
|
|
|
| 15 |
{%- set truncate_history_thinking = truncate_history_thinking if truncate_history_thinking is defined else True %}
|
| 16 |
|
| 17 |
{%- set ns = namespace(last_user_idx = -1) %}
|
|
|
|
| 12 |
{%- endmacro -%}
|
| 13 |
{%- set enable_thinking = enable_thinking if enable_thinking is defined else True %}
|
| 14 |
{%- set low_effort = low_effort if low_effort is defined else False %}
|
| 15 |
+
{%- if reasoning_effort is defined and reasoning_effort is not none %}
|
| 16 |
+
{%- set low_effort = reasoning_effort == "low" %}
|
| 17 |
+
{%- endif %}
|
| 18 |
{%- set truncate_history_thinking = truncate_history_thinking if truncate_history_thinking is defined else True %}
|
| 19 |
|
| 20 |
{%- set ns = namespace(last_user_idx = -1) %}
|