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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
| { | |
| "version": "1.0", | |
| "truncation": null, | |
| "padding": null, | |
| "added_tokens": [ | |
| { | |
| "id": 0, | |
| "content": "<|endoftext|>", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| { | |
| "id": 1, | |
| "content": "<|quantum|>", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| }, | |
| { | |
| "id": 2, | |
| "content": "<|classical|>", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| } | |
| ], | |
| "normalizer": { | |
| "type": "Sequence", | |
| "normalizers": [ | |
| { | |
| "type": "NFC" | |
| }, | |
| { | |
| "type": "Prepend", | |
| "prepend": "▁" | |
| } | |
| ] | |
| }, | |
| "pre_tokenizer": { | |
| "type": "Sequence", | |
| "pretokenizers": [ | |
| { | |
| "type": "Split", | |
| "pattern": { | |
| "Regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+" | |
| }, | |
| "behavior": "Isolated", | |
| "invert": false | |
| } | |
| ] | |
| }, | |
| "post_processor": { | |
| "type": "TemplateProcessing", | |
| "single": [ | |
| { | |
| "SpecialToken": { | |
| "id": "<|endoftext|>", | |
| "ids": [0] | |
| } | |
| } | |
| ], | |
| "pair": [ | |
| { | |
| "SpecialToken": { | |
| "id": "<|endoftext|>", | |
| "ids": [0] | |
| } | |
| } | |
| ], | |
| "special_tokens": { | |
| "<|endoftext|>": { | |
| "id": 0, | |
| "ids": [0] | |
| }, | |
| "<|quantum|>": { | |
| "id": 1, | |
| "ids": [1] | |
| }, | |
| "<|classical|>": { | |
| "id": 2, | |
| "ids": [2] | |
| } | |
| } | |
| }, | |
| "decoder": { | |
| "type": "Sequence", | |
| "decoders": [ | |
| { | |
| "type": "Replace", | |
| "pattern": { | |
| "String": "▁" | |
| }, | |
| "content": " " | |
| } | |
| ] | |
| }, | |
| "model": { | |
| "type": "BPE", | |
| "dropout": null, | |
| "unk_token": null, | |
| "continuing_subword_prefix": null, | |
| "end_of_word_suffix": null, | |
| "fuse_unk": false, | |
| "byte_fallback": false, | |
| "vocab": {}, | |
| "merges": [] | |
| } | |
| } |