Instructions to use allenai/OLMo-2-0425-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/OLMo-2-0425-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="allenai/OLMo-2-0425-1B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-2-0425-1B") model = AutoModelForCausalLM.from_pretrained("allenai/OLMo-2-0425-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use allenai/OLMo-2-0425-1B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "allenai/OLMo-2-0425-1B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "allenai/OLMo-2-0425-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/allenai/OLMo-2-0425-1B
- SGLang
How to use allenai/OLMo-2-0425-1B 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-2-0425-1B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "allenai/OLMo-2-0425-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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-2-0425-1B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "allenai/OLMo-2-0425-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use allenai/OLMo-2-0425-1B with Docker Model Runner:
docker model run hf.co/allenai/OLMo-2-0425-1B
Availability of OLMo-2 Models in Original Format?
Are there any OLMo-2 models available in their original format after training? The ones uploaded here (stage1-step0-tokens0B, stage1-step300-tokens1B, stage1-step10000-tokens21B, etc. ) follow the Hugging Face format, which I believe can’t be used directly as a training checkpoint when specifying the load_path flag in a training config (e.g. https://github.com/allenai/OLMo/blob/main/configs/official-0425/OLMo2-1B-stage1.yaml when training with https://github.com/allenai/OLMo/blob/main/scripts/train.py), though please correct me if that is actually possible.
I’m ideally looking for a non-sharded format with the files:
config.yaml
model.pt
optim.pt
train.pt
Thanks in advance!
Hey @suzeva , you can find links of checkpoints here: https://github.com/allenai/OLMo/blob/main/configs/official-0425/OLMo-2-0425-1B.csv in the same unsharded format you are looking for.
Thanks so much! That was exactly what I needed