NeMo Framework Megatron Backend

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NeMo Framework Megatron Backend

NVIDIA NeMo™ framework Megatron backend supports pre-training, post-training, and reinforcement learning of LLMs and multi-modal generative AI models with state-of-the-art data processing, model training techniques, and flexible deployment options.

NVIDIA AI Enterprise Supported

Layer	Label		Created
sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1	RUN	`NEMO_VERSION=1.14.0 rm -rf /opt/conda/pkgs/conda-4.11.0-py38h578d9bd_0/info/test/tests/data/env_metadata/`	01/04/2023 7:14 PM UTC
sha256:56cb85a5daddf43e0730558f2a698231d7e4de2c5e387a15166a0c0074485508	RUN	`NEMO_VERSION=1.14.0 printf "#!/bin/bash\njupyter lab --no-browser --allow-root --ip=0.0.0.0" >> start-jupyter.sh && chmod +x start-jupyter.sh`	01/04/2023 7:14 PM UTC
sha256:730db5bb5b6dc2d84109563bd02fab1739a8757819fff41f297fd711dfa91b1a	COPY	`tutorials /workspace/nemo/tutorials`	01/04/2023 7:14 PM UTC
sha256:c9a89a4296894db521210caad9282462e70beb9f2b6ab7364698e26c140f9d49	COPY	`tests /workspace/nemo/tests`	01/04/2023 7:14 PM UTC
sha256:b48c9bbdda1df3948f8c2e5c64475ff4141f6e14cb7797fb49c6ce252e9c956d	COPY	`examples /workspace/nemo/examples`	01/04/2023 7:14 PM UTC
sha256:b716bd486edd7e88802d176ed15bd10e2ee474b048708b6cd183ea83b40dc5a1	COPY	`scripts /workspace/nemo/scripts`	01/04/2023 7:14 PM UTC
sha256:bdb2addd6c2ac9de4a959742c033e565e00cf26d1d658a1321c8646d064aa0d8	WORKDIR	`/workspace/nemo`	01/04/2023 7:14 PM UTC
sha256:7a8b2e7a4f633c10784f5d454bdc9477b5c96243e80f683da6f7fac374c6bfa0	RUN	`NEMO_VERSION=1.14.0 pip install numba==0.53.1`	01/04/2023 7:14 PM UTC
sha256:8551c14f60dacdaf4e0696796fa47ecb6929be52addbcc81ff87fafa9c726ccc	RUN	`NEMO_VERSION=1.14.0 python -c "import nemo.collections.nlp as nemo_nlp" && python -c "import nemo.collections.tts as nemo_tts" && python -c "import nemo_text_processing.text_normalization as text_normalization"`	01/04/2023 7:14 PM UTC
sha256:ca032667f045dbccf026450b989fcc9597db3a0e6f14fbade873c97c71878534	RUN	`NEMO_VERSION=1.14.0 cd /tmp/nemo && pip install ".[all]"`	01/04/2023 7:14 PM UTC