Text Generation
Transformers
PyTorch
neuralquantum_nqlm
quantum
nlp
language-model
neural-quantum
hybrid-computing
custom_code
Instructions to use NeuralQuantum/nqlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeuralQuantum/nqlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="NeuralQuantum/nqlm", trust_remote_code=True)# Load model directly from transformers import NeuralQuantumNQLM model = NeuralQuantumNQLM.from_pretrained("NeuralQuantum/nqlm", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use NeuralQuantum/nqlm with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NeuralQuantum/nqlm" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NeuralQuantum/nqlm", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/NeuralQuantum/nqlm
- SGLang
How to use NeuralQuantum/nqlm 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 "NeuralQuantum/nqlm" \ --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": "NeuralQuantum/nqlm", "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 "NeuralQuantum/nqlm" \ --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": "NeuralQuantum/nqlm", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use NeuralQuantum/nqlm with Docker Model Runner:
docker model run hf.co/NeuralQuantum/nqlm
Add tokenizer_config.json
Browse files- tokenizer_config.json +25 -0
tokenizer_config.json
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{
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"tokenizer_class": "NeuralQuantumTokenizer",
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"auto_map": {
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"AutoTokenizer": "tokenization_nqlm.NeuralQuantumTokenizer"
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},
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"vocab_size": 50257,
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"model_max_length": 512,
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"padding_side": "right",
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"truncation_side": "right",
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"special_tokens": {
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"bos_token": "<|endoftext|>",
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"eos_token": "<|endoftext|>",
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"unk_token": "<|endoftext|>",
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"pad_token": "<|endoftext|>",
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"quantum_token": "<|quantum|>",
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"classical_token": "<|classical|>"
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},
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"clean_up_tokenization_spaces": true,
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"model_input_names": [
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"input_ids",
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"attention_mask"
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],
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"quantum_enhanced": true,
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"quantum_token_processing": true
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}
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