transformer-tricks 0.1.14

A collection of tricks to speed up LLMs, see our transformer-tricks papers on arXiv

Setup

pip3 install transformer-tricks

To run llama and other LLMs that need an agreement (not SmolLM), you first have to type the following, which will ask for your hf_token:

huggingface-cli login

Example

The example below converts SmolLM-135M to FlashNorm and measures perplexity of the original and the modified model.

import transformer_tricks as tt

# convert model and store the new model in ./SmolLM-135M_flashNorm
tt.flashify_repo('HuggingFaceTB/SmolLM-135M')

# run example inference of original and modified model
tt.hello_world('HuggingFaceTB/SmolLM-135M')
tt.hello_world('SmolLM-135M_flashNorm')

# measure perplexity of original and modified model
tt.perplexity('HuggingFaceTB/SmolLM-135M', speedup=16)
tt.perplexity('SmolLM-135M_flashNorm', speedup=16)

Results:

Once upon a time there was a curious little girl
Once upon a time there was a curious little girl
ppl: tensor(16.0831)
ppl: tensor(16.0831)

Test FlashNorm

# setup
git clone https://github.com/OpenMachine-ai/transformer-tricks.git
cd python
pip3 install --quiet -r requirements.txt

# run tests
python3 flashNorm_test.py

Results:

Once upon a time there was a curious little girl
Once upon a time there was a curious little girl
Once upon a time there was a little girl named
Once upon a time there was a little girl named
ppl: tensor(16.0831)
ppl: tensor(16.0831)
ppl: tensor(12.0864)
ppl: tensor(12.0864)

Notes on python package

• Link to package here
• Link to stats here