Instructions to use allenai/OLMo-2-1124-7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use allenai/OLMo-2-1124-7B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="allenai/OLMo-2-1124-7B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-2-1124-7B-Instruct")
model = AutoModelForCausalLM.from_pretrained("allenai/OLMo-2-1124-7B-Instruct")
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-2-1124-7B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "allenai/OLMo-2-1124-7B-Instruct"
# 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-2-1124-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/allenai/OLMo-2-1124-7B-Instruct

SGLang

How to use allenai/OLMo-2-1124-7B-Instruct 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-2-1124-7B-Instruct" \
    --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-2-1124-7B-Instruct",
		"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-2-1124-7B-Instruct" \
        --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-2-1124-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use allenai/OLMo-2-1124-7B-Instruct with Docker Model Runner:
```
docker model run hf.co/allenai/OLMo-2-1124-7B-Instruct
```

ValueError: Unrecognized model in allenai/OLMo-2-1124-7B-Instruct

by ryzzlestrizzle - opened Jun 12, 2025

Discussion

ryzzlestrizzle

Jun 12, 2025

I get this funky error when running the below code with transformers==4.52.4 and torch==2.7.1+cu126:

import torch
from transformers import AutoModelForCausalLM, __version__


print(torch.__version__)
print(f"Transformers version: {__version__}")


model_path = "allenai/OLMo-2-1124-7B-Instruct"
model = AutoModelForCausalLM.from_pretrained(model_path)

Any pointers on fixing? It works for the 1B instruct model (weirdly)

ryzzlestrizzle

Jun 12, 2025

Nevermind, the problem was some weird environment thing when running the Portuguese lm eval harness - problem nothing to do with the repo/code

ryzzlestrizzle changed discussion status to closed Jun 12, 2025

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment