Instructions to use Respair/NeMo_Canary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use Respair/NeMo_Canary with NeMo:
# tag did not correspond to a valid NeMo domain.
- Notebooks
- Google Colab
- Kaggle
| # Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import argparse | |
| import sys | |
| from nemo.deploy.multimodal import NemoQueryMultimodal | |
| def get_args(argv): | |
| parser = argparse.ArgumentParser( | |
| formatter_class=argparse.ArgumentDefaultsHelpFormatter, | |
| description=f"Query Triton Multimodal server", | |
| ) | |
| parser.add_argument("-u", "--url", default="0.0.0.0", type=str, help="url for the triton server") | |
| parser.add_argument("-mn", "--model_name", required=True, type=str, help="Name of the triton model") | |
| parser.add_argument("-mt", "--model_type", required=True, type=str, help="Type of the triton model") | |
| parser.add_argument("-int", "--input_text", required=True, type=str, help="Input text") | |
| parser.add_argument("-im", "--input_media", required=True, type=str, help="File path of input media") | |
| parser.add_argument("-bs", "--batch_size", default=1, type=int, help="Batch size") | |
| parser.add_argument("-mol", "--max_output_len", default=128, type=int, help="Max output token length") | |
| parser.add_argument("-tk", "--top_k", default=1, type=int, help="top_k") | |
| parser.add_argument("-tpp", "--top_p", default=0.0, type=float, help="top_p") | |
| parser.add_argument("-t", "--temperature", default=1.0, type=float, help="temperature") | |
| parser.add_argument("-rp", "--repetition_penalty", default=1.0, type=float, help="repetition_penalty") | |
| parser.add_argument("-nb", "--num_beams", default=1, type=int, help="num_beams") | |
| parser.add_argument("-it", "--init_timeout", default=60.0, type=float, help="init timeout for the triton server") | |
| parser.add_argument( | |
| "-lt", | |
| "--lora_task_uids", | |
| default=None, | |
| type=str, | |
| nargs="+", | |
| help="The list of LoRA task uids; use -1 to disable the LoRA module", | |
| ) | |
| args = parser.parse_args(argv) | |
| return args | |
| if __name__ == '__main__': | |
| args = get_args(sys.argv[1:]) | |
| nq = NemoQueryMultimodal(url=args.url, model_name=args.model_name, model_type=args.model_type) | |
| output = nq.query( | |
| input_text=args.input_text, | |
| input_media=args.input_media, | |
| batch_size=args.batch_size, | |
| max_output_len=args.max_output_len, | |
| top_k=args.top_k, | |
| top_p=args.top_p, | |
| temperature=args.temperature, | |
| repetition_penalty=args.repetition_penalty, | |
| num_beams=args.num_beams, | |
| init_timeout=args.init_timeout, | |
| lora_uids=args.lora_task_uids, | |
| ) | |
| print(output) | |