Folasaga
Fa'amatalaina AI (XAI) ua avea ma vaega taua o atina'e fa'aonaponei fa'aonaponei, e mafai ai e fa'alapotopotoga ona fa'atuatuaina ma malamalama i fa'ai'uga na faia e faiga fa'avae AI. Ae ui i lea, o le faʻatinoina o le XAI i faiga faʻapipiʻi lavelave e mafai ona avea ma se galuega faigata, aemaise lava pe a feagai ma atinaʻe tetele. I totonu o lenei tusiga, o le a tatou suʻesuʻeina pe faʻapefea ona faʻaogaina LangChain ma DSPy e tatala ai le mana o le XAI i le atinaʻeina o atinaʻe, e taulaʻi atu i le faia o filifiliga faʻavae AI.
O le a le Explainable AI (XAI)?
Fa'amatalaina AI e fa'atatau i le gafatia o faiga AI e tu'uina atu fa'amatalaga manino ma fa'amatalaina mo a latou fa'ai'uga ma valo'aga. E taua tele lenei mea i tulaga maualuga-siteki e pei o le soifua maloloina, tupe, ma felauaiga, lea e mafai ai e le AI ona i ai ni taunuuga taua.
LangChain: Ose Ta'iala mo le Fausiaina o Faiga Fa'amatalaga AI
LangChain o se faʻavae faʻavae mo le fausiaina o faʻamatalaga AI faʻamalamalamaina. E maua ai se seti o meafaigaluega ma faletusi mo le fatuina o faʻataʻitaʻiga e mafai ona tuʻuina atu faʻamatalaga manino ma faʻamatalaina mo a latou filifiliga. LangChain o loʻo fausia i luga o taʻutaʻua faʻavae aʻoaʻoga loloto e pei o TensorFlow ma PyTorch, faʻafaigofie ona tuʻufaʻatasia ma faiga AI o iai.
DSPy: O se Faletusi mo le Fausiaina o Faʻataʻitaʻiga AI Faʻamatalaina
DSPy o se faletusi mo le fausiaina o faʻataʻitaʻiga AI faʻamalamalamaina e faʻaaoga ai le PyTorch framework. O loʻo tuʻuina atu ai se seti o faʻataʻitaʻiga muamua ma meafaigaluega mo le fatuina o faʻamatalaga AI faʻamalamalamaga, e aofia ai faʻataʻitaʻiga mo le faʻavasegaina o ata, faʻaogaina o gagana masani, ma isi mea.
Faʻaaogaina AI Faʻamatalaina i le Atinaʻe Atinaʻe ma LangChain ma DSPy
O le faʻatinoina o le XAI i atinaʻe atinaʻe e manaʻomia ai se malamalamaga loloto i faiga faʻavae AI ma le mafai ona tuʻufaʻatasia vaega XAI i faiga o loʻo iai. O iinei, o le a matou suʻesuʻeina se faʻataʻitaʻiga faigofie o le faʻaogaina o le XAI i se faiga faʻapipiʻi lavelave e faʻaaoga ai LangChain ma DSPy.
Fa'ata'ita'iga: Fausiaina o se Fa'ata'ita'iga AI Fa'amatalaina mo le Fa'avasegaina o Ata
I lenei faʻataʻitaʻiga, o le a matou fausia se faʻataʻitaʻiga AI faʻamalamalamaina mo le faʻavasegaina o ata e faʻaaoga ai LangChain ma DSPy. O le a matou faʻaogaina se faʻaogaina faigofie fesoʻotaʻiga neural network (CNN) ma tuʻufaʻatasia vaega XAI e faʻaaoga ai LangChain.
sulu mai fafo
fa'aulufale mai sulu.nn pei nn
faaulufale mai le langchain
mai le langchain faaulufale mai LLAMA
# Fa'amatala le fausaga o le CNN
vasega CNN(nn.Module):
def __init__(self):
super(CNN, self).__init__()
self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
self.conv2 = nn.Conv2d(10, 20, kernel_size=5)
self.fc1 = nn.Linear(320, 50)
self.fc2 = nn.Linear(50, 10)
def i luma(tagata, x):
x = sulu.relu(self.conv1(x))
x = sulu.relu(self.conv2(x))
x = x.vaaiga(-1, 320)
x = sulu.relu(self.fc1(x))
x = tagata.fc2(x)
toe faafoi x
# Amata le ata CNN
fa'ata'ita'iga = CNN()
# Amata le faʻataʻitaʻiga LangChain LLAMA
llama = LLAMA(fa'ata'ita'iga)
# Fa'amatala le vaega XAI
vasega XAIComponent:
def __init__(self, model):
self.model = fa'ata'ita'iga
def fa'amatala(tagata, input_data):
# Faʻaaoga LangChain e faʻatupu ai se faʻamatalaga mo faʻamatalaga faʻapipiʻi
fa'amatalaga = llama.generate_explanation(input_data)
toe faafoi faamatalaga
# Amata le vaega XAI
xai_component = XAIComponent(fa'ata'ita'iga)
# Suʻe le vaega XAI
input_data = sulu.randn(1, 1, 28, 28)
fa'amatalaga = xai_component.explain(input_data)
lolomi(fa'amatalaga)
I lenei faʻataʻitaʻiga, matou te faʻamalamalamaina se faʻataʻitaʻiga CNN faigofie e faʻaaoga ai PyTorch ma faʻapipiʻi vaega XAI e faʻaaoga ai LangChain. Ona matou faʻamalamalamaina lea o se vaega XAI e faʻaaogaina LangChain e faʻatupu ai se faʻamatalaga mo faʻamatalaga faʻapipiʻi.
Top 5-10 Poloaiga/Snippets Tele Fa'aaogaina
O le pito i luga 5-10 pito sili ona faʻaaogaina poloaiga / snippets mo LangChain ma DSPy:
LangChain
langchain.LLAMA(model): Fa'amataina le LangChain LLAMA fa'ata'ita'iga.llama.generate_explanation(input_data): Faia se fa'amatalaga mo fa'amatalaga fa'aoga.langchain.Explanation(model, input_data): Fausia se mea fa'amatalaga mo fa'amatalaga fa'aoga.llama.explain(input_data): Fa'amatala fa'amatalaga fa'aoga e fa'aaoga ai le fa'ata'ita'iga LLAMA.langchain.ModelWrapper(model): Afifi le fa'ata'ita'iga i le afifi fa'ata'ita'iga a LangChain.
DSPy
dsp.DSPy(fa'ata'ita'iga): Fa'amataina se fa'ata'ita'iga DSPy.dsp.explain(input_data): Fa'amatala fa'amatalaga fa'aoga e fa'aaoga ai le fa'ata'ita'iga DSPy.dsp.ModelWrapper(model): afifi le fa'ata'ita'iga i le afifi fa'ata'ita'iga a DSPy.dsp.Explanation(model, input_data): Fausia se mea fa'amatalaga mo fa'amatalaga fa'aoga.dsp.generate_explanation(input_data): Fausia se fa'amatalaga mo fa'amatalaga o lo'o tu'uina.
Va'aiga
Ole fa'aaliga faigofie lea ole vaega XAI ile fa'aogaina ole Chart.js:
{
"type": "pa",
"fa'amatalaga": {
"labels": ["Input Data", "Faamatalaga"],
"fa'amaumauga": [
{
"label": "XAI Vaega",
"fa'amaumauga": [10, 20],
"Lulu lanu": [
"rgba(255, 99, 132, 0.2)",
"rgba(54, 162, 235, 0.2)"
],
"Lulu tuaoi": [
"rgba(255, 99, 132, 1)",
"rgba(54, 162, 235, 1)"
],
"BorderWidth": 1
}
]
},
"filifiliga": {
"fua": {
"yAxes": [
{
"tiki": {
"beginAtZero": moni
}
}
]
}
}
}
O lenei faʻaaliga o loʻo faʻaalia ai faʻamatalaga faʻapipiʻi ma le faʻamatalaga na faia e le vaega XAI.
Fa'ai'uga
O le faʻatinoina o le XAI i atinaʻe atinaʻe e manaʻomia ai se malamalamaga loloto i faiga faʻavae AI ma le mafai ona tuʻufaʻatasia vaega XAI i faiga o loʻo iai. LangChain ma DSPy e tuʻuina atu se seti o meafaigaluega ma faletusi mo le fausiaina o faʻamatalaga faʻamalamalamaga AI, faʻafaigofie ona faʻaogaina le XAI i faiga faʻapipiʻi lavelave. E ala i le mulimuli i le faʻataʻitaʻiga ma faʻaaliga o loʻo tuʻuina atu i lenei tusiga, e mafai e le au atinaʻe ona tatalaina le malosi o le XAI i totonu o latou atinaʻe atinaʻe ma fausia atili manino ma faʻamatalaina faiga faʻavae AI.
Galuega i le Lumanai
O galuega i le lumanaʻi i lenei autu e mafai ona aofia ai:
- Faʻaleleia atili vaega XAI faʻaogaina LangChain ma DSPy.
- Tu'ufa'atasia vaega XAI ma isi auivi AI ma faletusi.
- Atinaʻeina o mea faigaluega faʻapitoa faʻapitoa mo vaega XAI.
- Faʻaaogaina le XAI i faiga faʻapitoa AI ma vaega.
Fa'asinomaga
- LangChain: https://langchain.dev/
- DSPy: https://dspy.dev/
- PyTorch: https://pytorch.org/
- TensorFlow: https://www.tensorflow.org/