ethzanalytics/gpt-j-6B-8bit-sharded

This is a version of hivemind/gpt-j-6B-8bit for low-RAM loading, i.e., free Colab runtimes :)

• shards are <= 1000MB each
• a demo notebook of how to use it is here

Please refer to the original model card for hivemind/gpt-j-6B-8bit for all details.

Usage

NOTE: PRIOR to loading the model, you need to "patch" it to be compatible with loading 8bit weights etc. See the original model card above for details on how to do this.

install transformers, accelerate, and bitsandbytes if needed:

pip install transformers accelerate bitsandbytes

Patch the model, load using device_map="auto":

import transformers 
from transformers import AutoTokenizer

"""
CODE TO PATCH GPTJForCausalLM GOES HERE
"""

tokenizer = AutoTokenizer.from_pretrained("ethzanalytics/gpt-j-6B-8bit-sharded")

model = GPTJForCausalLM.from_pretrained(
    "ethzanalytics/gpt-j-6B-8bit-sharded",
    device_map="auto",
)

Take a look at the notebook for details.