Text Generation
Transformers
Safetensors
Korean
English
nova_gdn2
nova
gdn2
gated-deltanet
hybrid
korean
custom_code
Instructions to use Insightnova/Nova-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Insightnova/Nova-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Insightnova/Nova-1B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Insightnova/Nova-1B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Insightnova/Nova-1B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Insightnova/Nova-1B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Insightnova/Nova-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Insightnova/Nova-1B
- SGLang
How to use Insightnova/Nova-1B 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 "Insightnova/Nova-1B" \ --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": "Insightnova/Nova-1B", "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 "Insightnova/Nova-1B" \ --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": "Insightnova/Nova-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Insightnova/Nova-1B with Docker Model Runner:
docker model run hf.co/Insightnova/Nova-1B
Download export_manifest.json from Insightnova/Nova-1B: direct link, hf CLI and curl.
- Browser
- Download file 3.68 kB
-
https://huggingface.co/Insightnova/Nova-1B/resolve/main/export_manifest.json
- Command line
-
hf download hf://Insightnova/Nova-1B/export_manifest.json
-
curl -L -o export_manifest.json https://huggingface.co/Insightnova/Nova-1B/resolve/main/export_manifest.json
3.68 kB
| { | |
| "metadata_only": false, | |
| "tensor_count": 431, | |
| "weights_precision": "preserved without casting", | |
| "files": { | |
| "LICENSE": { | |
| "bytes": 11560, | |
| "sha256": "3ddf9be5c28fe27dad143a5dc76eea25222ad1dd68934a047064e56ed2fa40c5" | |
| }, | |
| "README.md": { | |
| "bytes": 20543, | |
| "sha256": "fa85c2fceac2b4117ff9238409d88b84c19a3ebc3faf6226e0519270fb946992" | |
| }, | |
| "SOURCE_PROVENANCE.json": { | |
| "bytes": 2199, | |
| "sha256": "f4c0c804de4a0272d1426b46f4fb482cf431e6736eaede1e19f307b49ec242ce" | |
| }, | |
| "THIRD_PARTY_NOTICES.txt": { | |
| "bytes": 2486, | |
| "sha256": "9225b393cdf36de03474bbb9559010efc6aad0141492d64ab45cf3713346365d" | |
| }, | |
| "architecture.py": { | |
| "bytes": 7724, | |
| "sha256": "df27fa8146cebf2d9655acd8b0571f774d113f6911ea3f9ea5b4e3da70b0615d" | |
| }, | |
| "architecture_config.py": { | |
| "bytes": 1977, | |
| "sha256": "bc2f96f5e88dbbffe83f571e093764d5e7ca3312f5623042111aa34f44eb9424" | |
| }, | |
| "config.json": { | |
| "bytes": 1401, | |
| "sha256": "ab51c7c75040562cf4cc3398d5d3bedce361781c068dc0e04360560f011e5852" | |
| }, | |
| "configuration_nova.py": { | |
| "bytes": 3072, | |
| "sha256": "781397ed279b22d9a703b54e70e84da3ccd62a035a806c470dbeb8cfbc783e9c" | |
| }, | |
| "cpu_backend.py": { | |
| "bytes": 12809, | |
| "sha256": "4330dc7349d6008d943e9ae5f463258bf97c32b74fc054772caddc84f633d253" | |
| }, | |
| "fast_decode.py": { | |
| "bytes": 4336, | |
| "sha256": "07d8fda5b92bdd96180a265b6ca66fcd19ab2e110576ce9e34fa2a98d19ad5d8" | |
| }, | |
| "gdn2.py": { | |
| "bytes": 11460, | |
| "sha256": "5408fa540c75e88d1930dfb6a711b342a662a1c84e0884267026d4de483ad4d9" | |
| }, | |
| "gdn2_spec.py": { | |
| "bytes": 2635, | |
| "sha256": "276ff07404fec37ae3e36e96871c09b30959bf12850d6a26ce363de3c4fbe20f" | |
| }, | |
| "generation_config.json": { | |
| "bytes": 143, | |
| "sha256": "99ed2196e2be9bc224518b7e8423f55b32eb1868a395fea92dddf051a44ce901" | |
| }, | |
| "generation_nova.py": { | |
| "bytes": 5033, | |
| "sha256": "dc50ba705274fcd965a61dd0f43dec3b863fe6ffb511adfb143e271e3402bd17" | |
| }, | |
| "model-00001-of-00005.safetensors": { | |
| "bytes": 996079960, | |
| "sha256": "8867b2abf66acd575d86aa5f90d7e7dad94ae577eec35c173c7c4b573f8f5cf0" | |
| }, | |
| "model-00002-of-00005.safetensors": { | |
| "bytes": 996086272, | |
| "sha256": "962694e507fb328a6567920068966925bb0ea38bd27ed8fe517086167a12bee4" | |
| }, | |
| "model-00003-of-00005.safetensors": { | |
| "bytes": 997689400, | |
| "sha256": "0da1c0b7af39ea25ee617faabdf1c7d0227a211b580c40a5a113d738ec85e567" | |
| }, | |
| "model-00004-of-00005.safetensors": { | |
| "bytes": 969295864, | |
| "sha256": "b8c578530eae6294770ea2881aae7c9455c38f74a715e94fa7c1d4e96cf4b2b9" | |
| }, | |
| "model-00005-of-00005.safetensors": { | |
| "bytes": 923460096, | |
| "sha256": "1f1ba1f6e346a58b58d00a8d51da420c4b0e565b7b10b0e3494ded85ccab03e7" | |
| }, | |
| "model.safetensors.index.json": { | |
| "bytes": 38476, | |
| "sha256": "b2680143fc15acb5965d8785170f8a76e968f6777c1022fc1ae3abcccffb5d94" | |
| }, | |
| "modeling_nova.py": { | |
| "bytes": 16797, | |
| "sha256": "2144598be96b70d9c217c1867afc9a111d89ccfcf1ce9e1cf02b19ebffdee0da" | |
| }, | |
| "sequence_utils.py": { | |
| "bytes": 1497, | |
| "sha256": "8214a6627b12a96d42e48427faeb4f17b5eafda0528847f643907247f442ffbe" | |
| }, | |
| "special_tokens_map.json": { | |
| "bytes": 563, | |
| "sha256": "9c5b7b7b9d61204f14b51a10bd355dbe9e6efdcc4aedd0999c6f19cfc476d367" | |
| }, | |
| "tokenizer.json": { | |
| "bytes": 5294784, | |
| "sha256": "7ec8609ea01904c068812e66c2a17450097088f975e05c26b31d0d582a0f713b" | |
| }, | |
| "tokenizer_config.json": { | |
| "bytes": 12253, | |
| "sha256": "dcce6daa10d0de1674a0dd640aeb23ba94900cd29b37bf7281926cf9a5c688d4" | |
| } | |
| } | |
| } | |