Instructions to use allenai/Olmo-3.1-32B-Think with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use allenai/Olmo-3.1-32B-Think with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="allenai/Olmo-3.1-32B-Think")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("allenai/Olmo-3.1-32B-Think")
model = AutoModelForCausalLM.from_pretrained("allenai/Olmo-3.1-32B-Think")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use allenai/Olmo-3.1-32B-Think with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "allenai/Olmo-3.1-32B-Think"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "allenai/Olmo-3.1-32B-Think",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/allenai/Olmo-3.1-32B-Think

SGLang

How to use allenai/Olmo-3.1-32B-Think 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 "allenai/Olmo-3.1-32B-Think" \
    --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": "allenai/Olmo-3.1-32B-Think",
		"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 "allenai/Olmo-3.1-32B-Think" \
        --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": "allenai/Olmo-3.1-32B-Think",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use allenai/Olmo-3.1-32B-Think with Docker Model Runner:
```
docker model run hf.co/allenai/Olmo-3.1-32B-Think
```

`git clone` fails with `fatal: expected 'packfile'

by douganger - opened 23 days ago

Discussion

douganger

23 days ago

•

edited 23 days ago

I’m trying to clone this repo on macOS and Git fails before receiving the packfile:

git clone https://huggingface.co/allenai/Olmo-3.1-32B-Think

Output:

Cloning into 'Olmo-3.1-32B-Think'...
fatal: expected 'packfile'

Environment:

macOS: 26.4.1 (25E253)
git: 2.50.1 (Apple Git-155)
git-lfs: git-lfs/3.7.1 (GitHub; darwin arm64; go 1.25.3)
git-xet: git-xet 0.2.1

I set GIT_TRACE=1 GIT_CURL_VERBOSE=1 and found that the clone is failing after a successful HTTP/2 200 response from /git-upload-pack.

The final upload-pack response includes:

HTTP/2 200
content-type: application/x-git-upload-pack-result
content-length: 0

Git then exits with: fatal: expected 'packfile'

From the client trace, it looks like Git is receiving an empty result where it expects the packfile.

Is this repo expected to be cloneable via Git, or should users prefer hf download for this model?

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