Text Generation
Transformers
Safetensors
English
qwen2
chat
conversational
text-generation-inference
Instructions to use divaspoudel/iol-2026-solver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use divaspoudel/iol-2026-solver with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="divaspoudel/iol-2026-solver") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("divaspoudel/iol-2026-solver") model = AutoModelForCausalLM.from_pretrained("divaspoudel/iol-2026-solver", 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use divaspoudel/iol-2026-solver with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "divaspoudel/iol-2026-solver" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "divaspoudel/iol-2026-solver", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/divaspoudel/iol-2026-solver
- SGLang
How to use divaspoudel/iol-2026-solver 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 "divaspoudel/iol-2026-solver" \ --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": "divaspoudel/iol-2026-solver", "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 "divaspoudel/iol-2026-solver" \ --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": "divaspoudel/iol-2026-solver", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use divaspoudel/iol-2026-solver with Docker Model Runner:
docker model run hf.co/divaspoudel/iol-2026-solver
Commit History
-
Update script.py
Verified signature9dfc51c -
Update script.py
Verified signaturea7c7e74
-
Update script.py
Verified signature0659241
-
Update script.py
Verified signature6e609e7 -
Update script.py
Verified signaturef2f18ce -
Update script.py
Verified signature4f28be1 -
Update script.py
Verified signature987de72 -
Update script.py
Verified signature3944e31 -
Update script.py
Verified signature34d8fbd -
Update script.py
Verified signature5f75ce6 -
Update script.py
Verified signature2b60086 -
Upload folder using huggingface_hub
Verified signaturea0caa2f -
Upload folder using huggingface_hub
Verified signature002913d -
Upload folder using huggingface_hub
Verified signaturee154bf4 -
Upload folder using huggingface_hub
Verified signatured4958fe
-
Upload folder using huggingface_hub
Verified signature05691dc -
Upload folder using huggingface_hub
Verified signature1ba446e -
Upload folder using huggingface_hub
Verified signaturea57f2b0 -
initial commit
Verified signature35f9d84