From 914bc409b0e1258db3980ff881a9d4beb6403fbd Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 21 Dec 2023 00:44:36 -0800 Subject: [PATCH] Bump transformers from 4.30.0 to 4.36.0 in /tools/ci_build (#18895) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Bumps [transformers](https://github.com/huggingface/transformers) from 4.30.0 to 4.36.0.
Release notes

Sourced from transformers's releases.

v4.36: Mixtral, Llava/BakLlava, SeamlessM4T v2, AMD ROCm, F.sdpa wide-spread support

New model additions

Mixtral

Mixtral is the new open-source model from Mistral AI announced by the blogpost Mixtral of Experts. The model has been proven to have comparable capabilities to Chat-GPT according to the benchmark results shared on the release blogpost.

The architecture is a sparse Mixture of Experts with Top-2 routing strategy, similar as NllbMoe architecture in transformers. You can use it through AutoModelForCausalLM interface:

>>> import torch
>>> from transformers import AutoModelForCausalLM,
AutoTokenizer

>>> model =
AutoModelForCausalLM.from_pretrained("mistralai/Mixtral-8x7B",
torch_dtype=torch.float16, device_map="auto")
>>> tokenizer =
AutoTokenizer.from_pretrained("mistralai/Mistral-8x7B")


>>> prompt = "My favourite condiment is"


>>> model_inputs = tokenizer([prompt],
return_tensors="pt").to(device)
>>> model.to(device)


>>> generated_ids = model.generate(**model_inputs,
max_new_tokens=100, do_sample=True)
>>> tokenizer.batch_decode(generated_ids)[0]

The model is compatible with existing optimisation tools such Flash Attention 2, bitsandbytes and PEFT library. The checkpoints are release under mistralai organisation on the Hugging Face Hub.

Llava / BakLlava

Llava is an open-source chatbot trained by fine-tuning LlamA/Vicuna on GPT-generated multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture. In other words, it is an multi-modal version of LLMs fine-tuned for chat / instructions.

The Llava model was proposed in Improved Baselines with Visual Instruction Tuning by Haotian Liu, Chunyuan Li, Yuheng Li and Yong Jae Lee.

The integration also includes BakLlava which is a Llava model trained with Mistral backbone.

The mode is compatible with "image-to-text" pipeline:

from transformers import pipeline
from PIL import Image
import requests

model_id = "llava-hf/llava-1.5-7b-hf"
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Commits

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Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- tools/ci_build/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tools/ci_build/requirements.txt b/tools/ci_build/requirements.txt index 96659d70af81f..aaca45b3e17e1 100644 --- a/tools/ci_build/requirements.txt +++ b/tools/ci_build/requirements.txt @@ -3,6 +3,6 @@ packaging protobuf==3.20.2 numpy==1.24.0 coloredlogs==15.0 -transformers==4.30.0 +transformers==4.36.0 psutil einops \ No newline at end of file