Instructions to use patrickvonplaten/opt_metaseq_6700m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickvonplaten/opt_metaseq_6700m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="patrickvonplaten/opt_metaseq_6700m")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("patrickvonplaten/opt_metaseq_6700m") model = AutoModel.from_pretrained("patrickvonplaten/opt_metaseq_6700m") - Notebooks
- Google Colab
- Kaggle
This repo let's you run the following checkpoint using facebookresearch/metaseq.
Do the following:
1. Install PyTorch
pip3 install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio==0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
2. Install Megatron
git clone https://github.com/patrickvonplaten/Megatron-LM.git
cd Megatron-LM
pip3 install six regex
pip3 install -e .
3. Install fairscale
git clone https://github.com/facebookresearch/fairscale.git
cd fairscale
git checkout prefetch_fsdp_params_simple
pip3 install -e .
4. Install metaseq
git clone https://github.com/patrickvonplaten/metaseq.git
cd metaseq
pip3 install -e .
5. Clone this repo (click top right on "How to clone")
6. Run the following:
cd <path/to/cloned/repo>
bash run.sh
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