| # Use the specified base image |
| FROM nvcr.io/nvidia/pytorch:23.12-py3 |
| |
| # Set the working directory to your project directory |
| WORKDIR ./ |
| |
| # Copy the contents of your project into the Docker image |
| COPY . . |
| |
| # Create and activate Conda environment |
| # RUN conda create --name plm python=3.10 |
| # SHELL ["conda", "run", "-n", "plm", "/bin/bash", "-c"] |
| # RUN conda activate plm |
| |
| # Install Miniconda |
| # RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh && \ |
| |
| |
| # ENV PATH="/opt/conda/bin:${PATH}" |
| |
| # Install dependencies |
| # RUN cd protein_lm/modeling/models/libs/ && pip install -e causal-conv1d && pip install -e mamba && cd ../../../../ |
| # RUN pip install transformers datasets accelerate evaluate pytest fair-esm biopython deepspeed |
| # RUN pip install -e . |
| # RUN pip install hydra-core --upgrade |
| # RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh |
| # source "$HOME/.cargo/env" |
| # RUN pip install -e protein_lm/tokenizer/rust_trie |
|
|
|
|
|
|
