Text Generation
Transformers
Safetensors
olmo3
code
livecodebench
sft
lora-merged
nothink
conversational
Instructions to use modrill/code-nothink-o7b-20260908 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use modrill/code-nothink-o7b-20260908 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="modrill/code-nothink-o7b-20260908") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("modrill/code-nothink-o7b-20260908") model = AutoModelForCausalLM.from_pretrained("modrill/code-nothink-o7b-20260908", 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]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use modrill/code-nothink-o7b-20260908 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "modrill/code-nothink-o7b-20260908" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "modrill/code-nothink-o7b-20260908", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/modrill/code-nothink-o7b-20260908
- SGLang
How to use modrill/code-nothink-o7b-20260908 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 "modrill/code-nothink-o7b-20260908" \ --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": "modrill/code-nothink-o7b-20260908", "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 "modrill/code-nothink-o7b-20260908" \ --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": "modrill/code-nothink-o7b-20260908", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use modrill/code-nothink-o7b-20260908 with Docker Model Runner:
docker model run hf.co/modrill/code-nothink-o7b-20260908
| { | |
| "chat_template_sha256": "03348cf1aab6c187117df83b81525a2c688934636a63b1c4a0acf9b2488c210e", | |
| "content_sha256": "33d099e5a93f3c02c042b149363879c5026a9abcd8e27d64cb20039c10fa08f2", | |
| "files": [ | |
| { | |
| "bytes": 1646, | |
| "path": "chat_template.jinja", | |
| "sha256": "03348cf1aab6c187117df83b81525a2c688934636a63b1c4a0acf9b2488c210e" | |
| }, | |
| { | |
| "bytes": 1631, | |
| "path": "config.json", | |
| "sha256": "c395e580e9e181b271048bbef57d0316ea7f2aea17761340c7cc6ccec6241119" | |
| }, | |
| { | |
| "bytes": 203, | |
| "path": "generation_config.json", | |
| "sha256": "1a9b3935357116c75f806d1defbd9893281a8f4a94aefeca708f31303e94aa7e" | |
| }, | |
| { | |
| "bytes": 916646, | |
| "path": "merges.txt", | |
| "sha256": "b6fe424e334903f7fb84d3a106d9730455f4744b9fe3c21ee136d97a00e72502" | |
| }, | |
| { | |
| "bytes": 581, | |
| "path": "special_tokens_map.json", | |
| "sha256": "78afb564e81264029b25f9caf24bda2521d5bdaeff5cd3fdbc01d3da2e8ce2f2" | |
| }, | |
| { | |
| "bytes": 7137177, | |
| "path": "tokenizer.json", | |
| "sha256": "73fd5254624f39a88e3faac6a8e11300fc3c735ed37880d4f4f08db898eaecca" | |
| }, | |
| { | |
| "bytes": 4319, | |
| "path": "tokenizer_config.json", | |
| "sha256": "e7ea56bef75ad5257b13dc09bfe3033e8cd742eb42233e9b57726d53be9f7ead" | |
| }, | |
| { | |
| "bytes": 1611056, | |
| "path": "vocab.json", | |
| "sha256": "9e14712c91b37c7aab74b1306baa46ac342d620637a4b44523cdc3aec7d24195" | |
| } | |
| ], | |
| "mode": "think", | |
| "schema": "CODE_SFT_TOKENIZER_RUNTIME_BUNDLE_V1", | |
| "source_repo": "allenai/Olmo-3-7B-Think", | |
| "source_revision": "d97e442d7cc678210054dbcc9b440894d62c89a4", | |
| "status": "COMPLETE", | |
| "tokenizer_sha256": "73fd5254624f39a88e3faac6a8e11300fc3c735ed37880d4f4f08db898eaecca" | |
| } | |