Instructions to use ffurfaro/Titans-OLMo-1B-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ffurfaro/Titans-OLMo-1B-hf with Transformers:

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

pipe = pipeline("text-generation", model="ffurfaro/Titans-OLMo-1B-hf")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ffurfaro/Titans-OLMo-1B-hf", dtype="auto")

PEFT
How to use ffurfaro/Titans-OLMo-1B-hf with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ffurfaro/Titans-OLMo-1B-hf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ffurfaro/Titans-OLMo-1B-hf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ffurfaro/Titans-OLMo-1B-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ffurfaro/Titans-OLMo-1B-hf

SGLang

How to use ffurfaro/Titans-OLMo-1B-hf 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 "ffurfaro/Titans-OLMo-1B-hf" \
    --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": "ffurfaro/Titans-OLMo-1B-hf",
		"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 "ffurfaro/Titans-OLMo-1B-hf" \
        --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": "ffurfaro/Titans-OLMo-1B-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ffurfaro/Titans-OLMo-1B-hf with Docker Model Runner:
```
docker model run hf.co/ffurfaro/Titans-OLMo-1B-hf
```

Improve model card: Add abstract and full paper title to link

by nielsr HF Staff - opened Sep 3, 2025

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

+12

-11

nielsr

Sep 3, 2025

This PR improves the model card for Titanesque-OLMo-1B-hf by:

Adding the full abstract of the paper, "TPTT: Transforming Pretrained Transformers into Titans", to provide comprehensive context and details about the model's architecture and experimental findings.
Updating the text of the existing paper link to include the full title [TPTT: Transforming Pretrained Transformers into Titans] for better clarity and discoverability.

The metadata, usage example, and existing badge links (including the arXiv link) remain unchanged as they are already accurate and comply with documentation guidelines and disclaimers.

Improve model card: Add abstract and full paper title to link4e65675e

ffurfaro changed pull request status to merged Sep 4, 2025

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