JAX weights converted from Torch checkpoint at facebook/galactica-30b.
(env) ubuntu@vm:~$ JAX_PLATFORM_NAME=cpu python3
>>> import jax
>>> print(jax.devices())
[CpuDevice(id=0)] # Ensure that model weights are loaded into CPU RAM, not accelerator memory.
>>> from transformers import FlaxOPTForCausalLM
>>> model = FlaxOPTForCausalLM.from_pretrained("facebook/galactica-30b", from_pt=True)
>>> model.push_to_hub(hf_model_repo)
Citation and Attribution
Citation from the original repo is reproduced below as per the cc-by-nc-4.0 licsense.
@inproceedings{GALACTICA,
title={GALACTICA: A Large Language Model for Science},
author={Ross Taylor and Marcin Kardas and Guillem Cucurull and Thomas Scialom and Anthony Hartshorn and Elvis Saravia and Andrew Poulton and Viktor Kerkez and Robert Stojnic},
year={2022}
}
Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC)
- Downloads last month
- 7
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.