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grant-rk's Projects

awesome-algorithm icon awesome-algorithm

代码模板、脑图、Top100高频LeetCode题 - 极简实用的算法和数据结构(持续更新中..)

bertweet icon bertweet

BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)

deep-live-cam icon deep-live-cam

real time face swap and one-click video deepfake with only a single image (uncensored)

dgl icon dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

firefly icon firefly

Firefly(流萤): 中文对话式大语言模型(全量微调+QLoRA),支持微调Aquila2、Baichuan2、CodeLlama、Llma2、Llama、Qwen、Baichuan、ChatGLM2、InternLM、Ziya、Bloom等大模型

kbqa-bert icon kbqa-bert

基于知识图谱的问答系统,BERT做命名实体识别和句子相似度,分为online和outline模式

leetcode icon leetcode

LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解,记录自己的leetcode解题之路。)

medicalgpt icon medicalgpt

MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training Pipeline. 训练医疗大模型,实现包括二次预训练、有监督微调、奖励建模、强化学习训练。

medusa icon medusa

Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads

megatron-lm icon megatron-lm

Ongoing research training transformer models at scale

mmf icon mmf

A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)

paddlenlp icon paddlenlp

An NLP library with Awesome pre-trained Transformer models and easy-to-use interface, supporting wide-range of NLP tasks from research to industrial applications.

python-girlfriend-mood icon python-girlfriend-mood

:kissing_closed_eyes: Analyze her mood through her girlfriend's words ·女朋友聊天时的情绪波动图谱,没女朋友的可自用(雾)。

research icon research

novel deep learning research works with PaddlePaddle

sincere icon sincere

Code for "Let's Stop Incorrect Comparisons in End-to-end Relation Extraction!", EMNLP 2020

target-offer icon target-offer

根据《剑指offer》中的题目,用python来进行编写

uie-acl-310 icon uie-acl-310

有一个通用实体关系事件抽取的任务,需要使用到UIE模框架,而且需要将起部署到昇腾310服务器上,因为UIE模型底层使用的是ernie3.0,但是目前paddle官方还不支持ernie3.0模型在昇腾310上部署,所以才有了以下的操作,主要过程是,先试用paddle训练处模型,然后使用 paddle2onnx.command.c_paddle_to_onnx方法将paddle的模型转为onnx模型 ,因现在的onnx模型是动态的shape和散乱的算子形态,需要使用paddle自带的工具paddle2onnx.optimize将onnx模型先进行重塑,固定好shape的维度,将散乱的算子进行整合,命令如下: $ python -m paddle2onnx.optimize --input_model /home/user/lijiaqi/PaddleNLP/model_zoo/uie/export_new/model.onnx --output_model /home/user/lijiaqi/model_new_uie.onnx --input_shape_dict "{'att_mask':[1,512],'pos_ids':[1,512],'token_type_ids':[1,512],'input_ids':[1,512]}" 然后将onnx模型在使用ATC工具转为acl所需要的om模型,这一步后面会讲。 另外在使用acl部署的时候,paddle框架是不能使用的,acl使用到的模型和训练过程均需要自己实现,包括from_pretrain阶段的分词,建立词表,数据处理部分,这部分我已经实现完,纯python版本的实现

wobert icon wobert

以词为基本单位的中文BERT

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