file_path stringlengths 3 280 | file_language stringclasses 66
values | content stringlengths 1 1.04M | repo_name stringlengths 5 92 | repo_stars int64 0 154k | repo_description stringlengths 0 402 | repo_primary_language stringclasses 108
values | developer_username stringlengths 1 25 | developer_name stringlengths 0 30 | developer_company stringlengths 0 82 |
|---|---|---|---|---|---|---|---|---|---|
tooling/tailwind/eslint.config.js | JavaScript | // FIXME: This kinda stinks...
/// <reference types="../../tooling/eslint/types.d.ts" />
import baseConfig from "@acme/eslint-config/base";
export default [...baseConfig];
| ymc9/my-t3-turbo | 0 | TypeScript | ymc9 | Yiming Cao | zenstackhq | |
tooling/tailwind/native.ts | TypeScript | import type { Config } from "tailwindcss";
import base from "./base";
export default {
content: base.content,
presets: [base],
theme: {},
} satisfies Config;
| ymc9/my-t3-turbo | 0 | TypeScript | ymc9 | Yiming Cao | zenstackhq | |
tooling/tailwind/web.ts | TypeScript | import type { Config } from "tailwindcss";
import animate from "tailwindcss-animate";
import base from "./base";
export default {
content: base.content,
presets: [base],
theme: {
container: {
center: true,
padding: "2rem",
screens: {
"2xl": "1400px",
},
},
extend: {
... | ymc9/my-t3-turbo | 0 | TypeScript | ymc9 | Yiming Cao | zenstackhq | |
turbo/generators/config.ts | TypeScript | import { execSync } from "node:child_process";
import type { PlopTypes } from "@turbo/gen";
interface PackageJson {
name: string;
scripts: Record<string, string>;
dependencies: Record<string, string>;
devDependencies: Record<string, string>;
}
export default function generator(plop: PlopTypes.NodePlopAPI): vo... | ymc9/my-t3-turbo | 0 | TypeScript | ymc9 | Yiming Cao | zenstackhq | |
scripts/ceval/eval.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import argparse
import pandas as pd
import torch
import json
from llama_evaluator import Llama_Evaluator
import time
choices = ["A", "B", "C", "D"]
def main(args, evaluator,take):
assert os.path.exists("subject_mapping.json"... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/ceval/evaluator.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import string
class Evaluator:
def __init__(self, choices, model_name, k=-1):
self.choices = choices
self.model_name = model_name
self.k = k
self.puncs = list(string.punctuation)
def format_example(s... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/ceval/llama_evaluator.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import re
from tqdm import tqdm
import random
import numpy as np
import torch
from transformers import LlamaForCausalLM, LlamaTokenizer
from evaluator import Evaluator
class Llama_Evaluator(Evaluator):
def __init__(self, choi... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/crawl_prompt.py | Python | import openai
import sys
import random
openai.api_key = "" # you must provide your OpenAI API key before crawling
if not openai.api_key:
raise ValueError("OpenAI API key not provided. Please set the 'openai.api_key' variable.")
def return_random_prompt():
system_prompt = "你需要尽可能给出多样化的任务指令和对应的回答。我们将用于人工评估ChatGPT... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/inference/gradio_demo.py | Python | import torch
from transformers import (
LlamaForCausalLM,
LlamaTokenizer,
StoppingCriteria,
)
import gradio as gr
import argparse
import os
from queue import Queue
from threading import Thread
import traceback
import gc
# Parse command-line arguments
parser = argparse.ArgumentParser()
parser.add_argument(
... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/inference/inference_hf.py | Python | import argparse
import json, os
parser = argparse.ArgumentParser()
parser.add_argument('--base_model', default=None, type=str, required=True)
parser.add_argument('--lora_model', default=None, type=str,help="If None, perform inference on the base model")
parser.add_argument('--tokenizer_path',default=None,type=str)
pars... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/inference/patches.py | Python | import torch
from torch import nn
from typing import Optional, Tuple, Union
import transformers
from transformers.models.llama.modeling_llama import apply_rotary_pos_emb, rotate_half
import math
try:
from xformers import ops as xops
except ImportError:
xops = None
print(
"Xformers is not installed ... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/langchain/langchain_qa.py | Python | import argparse
import os
parser = argparse.ArgumentParser()
parser.add_argument('--file_path',required=True,type=str)
parser.add_argument('--embedding_path',required=True,type=str)
parser.add_argument('--model_path',required=True,type=str)
parser.add_argument('--gpus', default="0", type=str)
parser.add_argument('--cha... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/langchain/langchain_sum.py | Python | import argparse
import os
parser = argparse.ArgumentParser()
parser.add_argument('--file_path',required=True,type=str)
parser.add_argument('--model_path',required=True,type=str)
parser.add_argument('--gpus', default="0", type=str)
parser.add_argument('--chain_type', default="refine", type=str)
args = parser.parse_args(... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/merge_llama_with_chinese_lora.py | Python | """
Usage:
python merge_llama_with_chinese_lora.py \
--base_model path/to/llama/model \
--lora_model path/to/first/lora/model [path/to/second/lora/model] \
--output_type [pth|huggingface] \
--output_dir path/to/output/dir
"""
import argparse
import json
import os
import gc
import torch
import peft
from... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/merge_llama_with_chinese_lora_low_mem.py | Python | """
Usage:
python merge_llama_with_chinese_lora_low_mem.py \
--base_model path/to/llama/model \
--lora_model path/to/first/lora[,path/to/second/lora] \
--output_type [pth|huggingface] \
--output_dir path/to/output/dir
"""
import argparse
import json
import os
import gc
import torch
import peft
from tra... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/merge_tokenizer/merge_tokenizers.py | Python | import os
os.environ["PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION"]="python"
from transformers import LlamaTokenizer
from sentencepiece import sentencepiece_model_pb2 as sp_pb2_model
import sentencepiece as spm
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--llama_tokenizer_dir', default=None, type... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/openai_server_demo/openai_api_protocol.py | Python | from typing import Optional, List, Dict, Any, Union
import time
import shortuuid
from pydantic import BaseModel, Field
class ChatCompletionRequest(BaseModel):
model: str = "chinese-llama-alpaca"
messages: Union[str, List[Dict[str, str]]]
temperature: Optional[float] = 0.7
top_p: Optional[float] = 1.0... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/openai_server_demo/openai_api_server.py | Python | import argparse
import os
from fastapi import FastAPI
import uvicorn
parser = argparse.ArgumentParser()
parser.add_argument('--base_model', default=None, type=str, required=True)
parser.add_argument('--lora_model', default=None, type=str,help="If None, perform inference on the base model")
parser.add_argument('--token... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/openai_server_demo/patches.py | Python | import torch
from torch import nn
from typing import Optional, Tuple, Union
import transformers
from transformers.models.llama.modeling_llama import apply_rotary_pos_emb, rotate_half
import math
try:
from xformers import ops as xops
except ImportError:
xops = None
print(
"Xformers is not installed ... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/build_dataset.py | Python | import logging
import os
from dataclasses import dataclass
from typing import Dict, Sequence, Union, List
import datasets
import torch
from datasets import load_dataset, concatenate_datasets
import transformers
IGNORE_INDEX = -100
logger = logging.getLogger('__name__')
PROMPT_TEMPLATE = (
"Below is an instr... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_clm_pt_with_peft.py | Python | #!/usr/bin/env python
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_clm_sft_with_peft.py | Python | #!/usr/bin/env python
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_pt.sh | Shell | lr=2e-4
lora_rank=8
lora_alpha=32
lora_trainable="q_proj,v_proj,k_proj,o_proj,gate_proj,down_proj,up_proj"
modules_to_save="embed_tokens,lm_head"
lora_dropout=0.05
pretrained_model=path/to/hf/llama/dir
chinese_tokenizer_path=path/to/chinese/llama/tokenizer/dir
dataset_dir=path/to/pt/data/dir
data_cache=temp_data_cache... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_sft.sh | Shell | lr=1e-4
lora_rank=8
lora_alpha=32
lora_trainable="q_proj,v_proj,k_proj,o_proj,gate_proj,down_proj,up_proj"
modules_to_save="embed_tokens,lm_head"
lora_dropout=0.05
pretrained_model=path/to/hf/llama/or/merged/llama/dir/or/model_id
chinese_tokenizer_path=path/to/chinese/llama/tokenizer/dir
dataset_dir=path/to/sft/data/d... | ymcui/Chinese-LLaMA-Alpaca | 18,964 | 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs) | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/ceval/eval.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import argparse
import pandas as pd
import torch
import json
from llama_evaluator import Llama_Evaluator
import time
choices = ["A", "B", "C", "D"]
def main(args, evaluator, take):
assert os.path.exists("subject_mapping.js... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/ceval/llama_evaluator.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import re
from tqdm import tqdm
import random
import numpy as np
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers import GenerationConfig
DEFAULT_SYSTEM_PROMPT = """You are a helpful as... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/cmmlu/categories.py | Python | # This code is modified from CMMLU Project: https://github.com/haonan-li/CMMLU
name_en2zh = {
"agronomy": "农学",
"anatomy": "解剖学",
"ancient_chinese": "古汉语",
"arts": "艺术学",
"astronomy": "天文学",
"business_ethics": "商业伦理",
"chinese_civil_service_exam": "中国公务员考试",
"chinese_driving_rule": "中国驾驶... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/cmmlu/eval.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import argparse
import pandas as pd
import torch
import json
from llama_evaluator import Llama_Evaluator
from glob import glob
import time
from collections import defaultdict
from categories import name_en2zh, subcategories, catego... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/cmmlu/llama_evaluator.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import re
from tqdm import tqdm
import random
import numpy as np
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers import GenerationConfig
DEFAULT_SYSTEM_PROMPT = """You are a helpful as... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/inference/inference_hf.py | Python | import argparse
import json, os
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers import GenerationConfig
from transformers import BitsAndBytesConfig
DEFAULT_SYSTEM_PROMPT = """You are a helpful assistant. 你是一个乐于助人的助手。"""
system_format='<|start_header_id|>system<|end_header_i... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/llama_cpp/chat.sh | Shell | #!/bin/bash
# script to chat with Llama-3-Chinese-Instruct model
# usage: ./chat.sh llama-3-chinese-instruct-gguf-model-path your-first-instruction
# WARNING: the hyperparameters are not optimal, please tune them yourself
FIRST_INSTRUCTION=$2
SYSTEM_PROMPT="You are a helpful assistant. 你是一个乐于助人的助手。"
./main -m $1 --c... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/longbench/eval.py | Python | # The script is from https://github.com/THUDM/LongBench
import os
import json
import argparse
import numpy as np
from metrics import (
qa_f1_score,
rouge_zh_score,
qa_f1_zh_score,
rouge_score,
classification_score,
retrieval_score,
retrieval_zh_score,
count_score,
code_sim_score,
)
... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/longbench/metrics.py | Python | # The script is from https://github.com/THUDM/LongBench
import re
import string
import jieba
from fuzzywuzzy import fuzz
import difflib
from collections import Counter
from rouge import Rouge
def normalize_answer(s):
"""Lower text and remove punctuation, articles and extra whitespace."""
def remove_articles... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/longbench/pred.py | Python | # The script is modified from https://github.com/THUDM/LongBench/blob/main/pred.py
from datasets import load_dataset
import torch
import random
import numpy as np
import json
from transformers import AutoTokenizer, AutoModelForCausalLM
from transformers import BitsAndBytesConfig
from tqdm import tqdm
import os
import a... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/merge_llama3_with_chinese_lora_low_mem.py | Python | """
Usage:
python merge_llama3_with_chinese_lora_low_mem.py \
--base_model path/to/llama-3-hf-model \
--lora_model path/to/llama-3-chinese-lora \
--output_type [huggingface|pth|] \
--output_dir path/to/output-dir
"""
import argparse
import json
import os
import gc
import torch
import peft
from transfor... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/mmlu/categories.py | Python | subcategories = {
"abstract_algebra": ["math"],
"anatomy": ["health"],
"astronomy": ["physics"],
"business_ethics": ["business"],
"clinical_knowledge": ["health"],
"college_biology": ["biology"],
"college_chemistry": ["chemistry"],
"college_computer_science": ["computer science"],
"c... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/mmlu/eval.py | Python | # modified from https://github.com/baichuan-inc/Baichuan-7B/blob/main/evaluation/evaluate_mmlu.py
import argparse
import os
import torch
import numpy as np
import pandas as pd
from categories import subcategories, categories
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
choices = ["A"... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/oai_api_demo/openai_api_protocol.py | Python | from typing import Optional, List, Dict, Any, Union, Literal
import time
import shortuuid
from pydantic import BaseModel, Field
class ChatCompletionRequest(BaseModel):
model: str = "llama-3-chinese"
messages: Union[str, List[Dict[str, str]]]
temperature: Optional[float] = 0.2
top_p: Optional[float] ... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/oai_api_demo/openai_api_server.py | Python | import argparse
import os
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
from threading import Thread
from sse_starlette.sse import EventSourceResponse
parser = argparse.ArgumentParser()
parser.add_argument('--base_model', default=None, type=str, required=True)
parser.add... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/build_dataset.py | Python | import logging
import os
from typing import Union, List
import datasets
import torch
from datasets import load_dataset, concatenate_datasets
import transformers
IGNORE_INDEX = -100
logger = logging.getLogger('__name__')
DEFAULT_SYSTEM_PROMPT = """You are a helpful assistant. 你是一个乐于助人的助手。"""
system_format='<|start_h... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_clm_pt_with_peft.py | Python | #!/usr/bin/env python
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_clm_sft_with_peft.py | Python | #!/usr/bin/env python
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_pt.sh | Shell | #!/bin/bash
## 运行脚本前请仔细阅读wiki(https://github.com/ymcui/Chinese-LLaMA-Alpaca-3/wiki/pt_scripts_zh)
## Read the wiki(https://github.com/ymcui/Chinese-LLaMA-Alpaca-3/wiki/pt_scripts_en) carefully before running the script
lr=1e-4
lora_rank=64
lora_alpha=128
lora_trainable="q_proj,v_proj,k_proj,o_proj,gate_proj,down_proj,u... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_sft.sh | Shell | #!/bin/bash
## 运行脚本前请仔细阅读wiki(https://github.com/ymcui/Chinese-LLaMA-Alpaca-3/wiki/sft_scripts_zh)
## Read the wiki(https://github.com/ymcui/Chinese-LLaMA-Alpaca-3/wiki/sft_scripts_en) carefully before running the script
lr=1e-4
lora_rank=64
lora_alpha=128
lora_trainable="q_proj,v_proj,k_proj,o_proj,gate_proj,down_proj... | ymcui/Chinese-LLaMA-Alpaca-3 | 1,964 | 中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3 | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/ceval/eval.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import argparse
import pandas as pd
import torch
import json
from mixtral_evaluator import Mixtral_Evaluator
import time
choices = ["A", "B", "C", "D"]
def main(args, evaluator,take):
assert os.path.exists("subject_mapping.j... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/ceval/evaluator.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import string
class Evaluator:
def __init__(self, choices, model_name, k=-1):
self.choices = choices
self.model_name = model_name
self.k = k
self.puncs = list(string.punctuation)
def format_example(s... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/ceval/mixtral_evaluator.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import re
from tqdm import tqdm
import random
import numpy as np
import torch
from transformers import AutoModelForCausalLM, LlamaTokenizer, BitsAndBytesConfig
from transformers import GenerationConfig
from evaluator import Evalua... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/cmmlu/categories.py | Python | # This code is modified from CMMLU Project: https://github.com/haonan-li/CMMLU
name_en2zh = {
"agronomy": "农学",
"anatomy": "解剖学",
"ancient_chinese": "古汉语",
"arts": "艺术学",
"astronomy": "天文学",
"business_ethics": "商业伦理",
"chinese_civil_service_exam": "中国公务员考试",
"chinese_driving_rule": "中国驾驶... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/cmmlu/eval.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import argparse
import pandas as pd
import torch
import json
from mxitral_evaluator import Mixtral_Evaluator
from glob import glob
import time
from collections import defaultdict
from categories import name_en2zh, subcategories, ca... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/cmmlu/evaluator.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import string
class Evaluator:
def __init__(self, choices, model_path, k=-1):
self.choices = choices
self.model_path = model_path
self.k = k
self.puncs = list(string.punctuation)
def format_example(se... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/cmmlu/mixtral_evaluator.py | Python | # This code is modified from C-Eval Project: https://github.com/SJTU-LIT/ceval
import os
import re
from tqdm import tqdm
import random
import numpy as np
import torch
from transformers import AutoModelForCausalLM, LlamaTokenizer, BitsAndBytesConfig
from transformers import GenerationConfig
from evaluator import Evalua... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/inference/inference_hf.py | Python | import argparse
import json, os
TEMPLATE = (
"[INST] {instruction} [/INST]"
)
parser = argparse.ArgumentParser()
parser.add_argument('--base_model', default=None, type=str, required=True)
parser.add_argument('--tokenizer_path', default=None, type=str)
parser.add_argument('--data_file', default=None, type=str, hel... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/llamacpp/chat.sh | Shell | #!/bin/bash
# script to chat with Chinese-Mixtral-Instruct model
# usage: ./chat.sh chinese-mixtral-instruct-gguf-model-path
# WARNING: the hyperparameters are not optimal, please tune them yourself
./main -m $1 --color --interactive-first \
-c 4096 -t 6 --temp 0.2 --repeat_penalty 1.1 -ngl 999 \
--in-prefix ' [INST]... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/longbench/eval.py | Python | # The script is from https://github.com/THUDM/LongBench
import os
import json
import argparse
import numpy as np
from metrics import (
qa_f1_score,
rouge_zh_score,
qa_f1_zh_score,
rouge_score,
classification_score,
retrieval_score,
retrieval_zh_score,
count_score,
code_sim_score,
)
... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/longbench/metrics.py | Python | # The script is from https://github.com/THUDM/LongBench
import re
import string
import jieba
from fuzzywuzzy import fuzz
import difflib
from collections import Counter
from rouge import Rouge
def normalize_answer(s):
"""Lower text and remove punctuation, articles and extra whitespace."""
def remove_articles... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/longbench/pred_mixtral.py | Python | # The script is modified from https://github.com/THUDM/LongBench/blob/main/pred.py
from datasets import load_dataset
import torch
import random
import numpy as np
import json
from transformers import LlamaTokenizer, AutoModelForCausalLM
from transformers import BitsAndBytesConfig
from tqdm import tqdm
import os
import ... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/merge_mixtral_with_chinese_lora_low_mem.py | Python | """
Usage:
python merge_mixtral_with_chinese_lora_low_mem.py \
--base_model path/to/Mixtral-8x7B-v0.1 \
--lora_model path/to/chinese-Mixtral-8x7B-v0.1-lora \
--output_dir path/to/output-dir
"""
import argparse
import json
import os
import gc
import torch
import peft
from transformers import LlamaTokenizer
... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/mmlu/categories.py | Python | subcategories = {
"abstract_algebra": ["math"],
"anatomy": ["health"],
"astronomy": ["physics"],
"business_ethics": ["business"],
"clinical_knowledge": ["health"],
"college_biology": ["biology"],
"college_chemistry": ["chemistry"],
"college_computer_science": ["computer science"],
"c... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/mmlu/eval.py | Python | # modified from https://github.com/baichuan-inc/Baichuan-7B/blob/main/evaluation/evaluate_mmlu.py
import argparse
import os
import torch
import numpy as np
import pandas as pd
from categories import subcategories, categories
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
choices = ["A"... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/openai_server_demo/openai_api_protocol.py | Python | from typing import Optional, List, Dict, Any, Union, Literal
import time
import shortuuid
from pydantic import BaseModel, Field
class ChatCompletionRequest(BaseModel):
model: str = "chinese-mixtral"
messages: Union[str, List[Dict[str, str]]]
temperature: Optional[float] = 0.2
top_p: Optional[float] ... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/openai_server_demo/openai_api_server.py | Python | import argparse
import os
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
from threading import Thread
from sse_starlette.sse import EventSourceResponse
parser = argparse.ArgumentParser()
parser.add_argument('--base_model', default=None, type=str, required=True)
parser.add... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/build_dataset.py | Python | import logging
import os
from typing import Union, List
import datasets
import torch
from datasets import load_dataset, concatenate_datasets
import transformers
IGNORE_INDEX = -100
logger = logging.getLogger('__name__')
PROMPT_TEMPLATE = (
"[INST] {instruction} [/INST]"
)
def build_instruction_dataset(... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_clm_pt_with_peft.py | Python | #!/usr/bin/env python
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_clm_sft_with_peft.py | Python | #!/usr/bin/env python
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_pt.sh | Shell |
## 运行脚本前请仔细阅读wiki(https://github.com/ymcui/Chinese-Mixtral/wiki/pt_scripts_zh)
## Read the wiki(https://github.com/ymcui/Chinese-Mixtral/wiki/pt_scripts_en) carefully before running the script
lr=1e-4
lora_rank=64
lora_alpha=128
lora_trainable="q_proj,v_proj,k_proj,o_proj,gate,w1,w2,w3"
modules_to_save="embed_tokens,l... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
scripts/training/run_sft.sh | Shell |
## 运行脚本前请仔细阅读wiki(https://github.com/ymcui/Chinese-Mixtral/wiki/sft_scripts_zh)
## Read the wiki(https://github.com/ymcui/Chinese-Mixtral/wiki/sft_scripts_en) carefully before running the script
lr=1e-4
lora_rank=64
lora_alpha=128
lora_trainable="q_proj,v_proj,k_proj,o_proj,gate,w1,w2,w3"
modules_to_save="embed_tokens... | ymcui/Chinese-Mixtral | 609 | 中文Mixtral混合专家大模型（Chinese Mixtral MoE LLMs） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/classifier_utils.py | Python | from absl import flags
import re
import numpy as np
import tensorflow as tf
from data_utils import SEP_ID, CLS_ID
FLAGS = flags.FLAGS
SEG_ID_A = 0
SEG_ID_B = 1
SEG_ID_CLS = 2
SEG_ID_SEP = 3
SEG_ID_PAD = 4
class PaddingInputExample(object):
"""Fake example so the num input examples is a multiple of the batch ... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/cmrc2018_evaluate_drcd.py | Python | # -*- coding: utf-8 -*-
'''
Evaluation script for CMRC 2018
version: v5
Note:
v5 formatted output, add usage description
v4 fixed segmentation issues
'''
from __future__ import print_function
from collections import Counter, OrderedDict
import string
import re
import argparse
import json
import sys
reload(sys)
sys.set... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/data_utils.py | Python | # -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import os
import random
from absl import flags
import absl.logging as _logging # pylint: disable=unused-import
import numpy as np
import tensorflow as tf
from prepro_u... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/function_builder.py | Python | """doc."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import functools
import os
import tensorflow as tf
import modeling
import xlnet
def construct_scalar_host_call(
monitor_dict,
model_dir,
prefix="",
reduce_fn=None):
"""
Construc... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/gpu_utils.py | Python | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import tensorflow as tf
def assign_to_gpu(gpu=0, ps_dev="/device:CPU:0"):
def _assign(op):
node_def = op if isinstance(op, tf.NodeDef) else op.node_def
if node_def.op == "Variable... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/model_utils.py | Python | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
import os
import re
import numpy as np
import six
from os.path import join
from six.moves import zip
from absl import flags
import tensorflow as tf
def configure_tpu(FLAGS):
if FLAGS.us... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/modeling.py | Python | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
def gelu(x):
"""Gaussian Error Linear Unit.
This is a smoother version of the RELU.
Original paper: https://arxiv.org/abs/1606.08415
Args:
x: float Tens... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/prepro_utils.py | Python | # coding=utf-8
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import unicodedata
import six
from functools import partial
SPIECE_UNDERLINE = '▁'
def printable_text(text):
"""Returns text encoded in a way suitable for print or `tf.logging`."""
# The... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/run_classifier.py | Python | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from os.path import join
from absl import flags
import os
import sys
import csv
import collections
import numpy as np
import time
import math
import json
import random
from copy import copy
from collections imp... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/run_cmrc_drcd.py | Python | # coding=utf-8
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from absl import flags
import absl.logging as _logging # pylint: disable=unused-import
import collections
import os
import time
import math
import json
import six
import random
import gc
impor... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/squad_utils.py | Python | """Official evaluation script for SQuAD version 2.0.
In addition to basic functionality, we also compute additional statistics and
plot precision-recall curves if an additional na_prob.json file is provided.
This file is expected to map question ID's to the model's predicted probability
that a question is unanswerable... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/summary.py | Python | # -*- coding: utf-8 -*-
'''
print summary
'''
from __future__ import print_function
from collections import Counter, OrderedDict
import string
import re
import argparse
import json
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import pdb
import os
import math
import numpy as np
import collections
from prettyta... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/tpu_estimator.py | Python | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/xlnet.py | Python | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import os
import tensorflow as tf
import modeling
def _get_initializer(FLAGS):
"""Get variable intializer."""
if FLAGS.init == "uniform":
initializer = tf.initializers.random_uniform(
... | ymcui/Chinese-XLNet | 1,650 | Pre-Trained Chinese XLNet（中文XLNet预训练模型） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/modeling.py | Python | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | ymcui/LERT | 221 | LERT: A Linguistically-motivated Pre-trained Language Model（语言学信息增强的预训练模型LERT） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/optimization.py | Python | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | ymcui/LERT | 221 | LERT: A Linguistically-motivated Pre-trained Language Model（语言学信息增强的预训练模型LERT） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/run.pretrain.sh | Shell | #!/bin/bash
set -ex
TPU_NAME="your-tpu-name"
TPU_ZONE="your-tpu-zone"
DATA_DIR=./your-path-to-tfrecords
MODEL_DIR=./your-path-to-model-saving
CONFIG_FILE=./your-path-to-config-file
# run pretraining
python run_pretraining.py \
--input_file=${DATA_DIR}/tf_examples.tfrecord.* \
--output_dir=${MODEL_DIR} \
--do_train... | ymcui/LERT | 221 | LERT: A Linguistically-motivated Pre-trained Language Model（语言学信息增强的预训练模型LERT） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/run_pretraining.py | Python | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | ymcui/LERT | 221 | LERT: A Linguistically-motivated Pre-trained Language Model（语言学信息增强的预训练模型LERT） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
src/tokenization.py | Python | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | ymcui/LERT | 221 | LERT: A Linguistically-motivated Pre-trained Language Model（语言学信息增强的预训练模型LERT） | Python | ymcui | Yiming Cui | Joint Laboratory of HIT and iFLYTEK Research (HFL) |
gatsby-config.js | JavaScript | require('dotenv').config()
module.exports = {
plugins: [
`gatsby-plugin-sharp`,
{
resolve: `gatsby-source-graphcms`,
options: {
downloadLocalImages: true,
endpoint: process.env.GRAPHCMS_ENDPOINT,
token: process.env.GRAPHCMS_TOKEN,
},
},
`gatsby-transformer-sh... | ynnoj/2020-07-17-gatsby-preview-graphcms | 1 | 📹 Preview GraphCMS content with Gatsby Cloud | JavaScript | ynnoj | Jonathan Steele | stripe |
src/pages/index.js | JavaScript | import React from 'react'
import { graphql } from 'gatsby'
import Img from 'gatsby-image'
function IndexPage({ data }) {
const { products } = data
return products.nodes.map((product) => (
<React.Fragment>
<h1 key={product.id}>{product.name}</h1>
{product.images.map((image) => (
<Img
... | ynnoj/2020-07-17-gatsby-preview-graphcms | 1 | 📹 Preview GraphCMS content with Gatsby Cloud | JavaScript | ynnoj | Jonathan Steele | stripe |
gatsby-browser.js | JavaScript | import React from 'react'
import { MDXProvider } from '@mdx-js/react'
const wrapRootElement = ({ element }) => {
return (
<MDXProvider
components={{
h2: (props) => <h2 style={{ color: 'blue' }} {...props} />,
p: (props) => <p style={{ color: 'red' }} {...props} />,
CTA: (props) => (... | ynnoj/2020-08-07-working-with-mdx-graphcms | 2 | 📹 Working with MDX and GraphCMS | JavaScript | ynnoj | Jonathan Steele | stripe |
gatsby-config.js | JavaScript | require('dotenv').config()
module.exports = {
plugins: [
'gatsby-plugin-mdx',
{
resolve: 'gatsby-source-graphcms',
options: {
endpoint: process.env.GRAPHCMS_ENDPOINT,
token: process.env.GRAPHCMS_TOKEN,
buildMarkdownNodes: true,
},
},
],
}
| ynnoj/2020-08-07-working-with-mdx-graphcms | 2 | 📹 Working with MDX and GraphCMS | JavaScript | ynnoj | Jonathan Steele | stripe |
src/pages/index.js | JavaScript | import React from 'react'
import { graphql } from 'gatsby'
import { MDXRenderer } from 'gatsby-plugin-mdx'
function IndexPage({ data }) {
const { posts } = data
return posts.nodes.map((post) => (
<div key={post.id}>
<h1>{post.title}</h1>
<MDXRenderer>{post.content.markdownNode.childMdx.body}</MDXR... | ynnoj/2020-08-07-working-with-mdx-graphcms | 2 | 📹 Working with MDX and GraphCMS | JavaScript | ynnoj | Jonathan Steele | stripe |
gatsby-browser.js | JavaScript | import React from 'react'
import {
ApolloClient,
ApolloProvider,
HttpLink,
InMemoryCache,
} from '@apollo/client'
import { MDXProvider } from '@mdx-js/react'
import fetch from 'isomorphic-fetch'
import './src/styles/index.css'
import Layout from './src/components/layout'
const httpLink = new HttpLink({
uri:... | ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
gatsby-config.js | JavaScript | require('dotenv').config()
module.exports = {
siteMetadata: {
title: 'GraphCMS Blog',
description:
'Gatsby blog starter for GraphCMS! Powered by `gatsby-source-graphcms`, featuring `gatsby-image` and MDX!',
keywords: 'Headless CMS, GraphCMS, GraphQL CMS, Gatsby',
},
plugins: [
'gatsby-plugi... | ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
gatsby-node.js | JavaScript | const path = require('path')
exports.createPages = async ({ actions: { createPage }, graphql }) => {
const { data } = await graphql(
`
{
pages: allGraphCmsPage {
nodes {
id
content {
markdownNode {
childMdx {
body
... | ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
gatsby-ssr.js | JavaScript | export { wrapPageElement, wrapRootElement } from './gatsby-browser'
| ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
postcss.config.js | JavaScript | module.exports = {
plugins: [require('postcss-preset-env'), require('tailwindcss')],
}
| ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
src/components/footer.js | JavaScript | import React from 'react'
import GitHubSVG from '../svg/github.svg'
import LinkedInSVG from '../svg/linkedin.svg'
import SlackSVG from '../svg/slack.svg'
import TwitterSVG from '../svg/twitter.svg'
const socialLinks = [
{
Component: GitHubSVG,
href: 'https://github.com/graphcms/gatsby-graphcms-ecommerce-sta... | ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
src/components/header.js | JavaScript | import React, { useEffect, useState } from 'react'
import { graphql, Link, useStaticQuery } from 'gatsby'
import { globalHistory, useLocation } from '@reach/router'
import cx from 'classnames'
import GraphCMSLogo from '../svg/logo.svg'
import GraphCMSMark from '../svg/mark.svg'
import Transition from './transition'
f... | ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
src/components/layout.js | JavaScript | import React from 'react'
import Footer from './footer'
import Header from './header'
import SEO from './seo'
function Layout({ children, pageContext: { page } }) {
return (
<React.Fragment>
<SEO {...page} />
<div className="flex flex-col min-h-screen">
<div className="flex-grow max-w-3xl mx... | ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
src/components/seo.js | JavaScript | import React from 'react'
import { graphql, useStaticQuery } from 'gatsby'
import { Helmet } from 'react-helmet'
function SEO({ title, seo }) {
const {
site: { siteMetadata },
} = useStaticQuery(graphql`
{
site {
siteMetadata {
description
keywords
title
... | ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
src/components/transition.js | JavaScript | import React, { useRef, useEffect, useContext } from 'react'
import { CSSTransition as ReactCSSTransition } from 'react-transition-group'
const TransitionContext = React.createContext({
parent: {},
})
function useIsInitialRender() {
const isInitialRender = useRef(true)
useEffect(() => {
isInitialRender.curr... | ynnoj/2020-08-28-dynamic-content-in-gatsby | 2 | 📹 Dynamic content in Gatsby with Apollo Client | JavaScript | ynnoj | Jonathan Steele | stripe |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.