模型:
KoichiYasuoka/deberta-base-thai-ud-goeswith
这是一个在泰文维基百科文本上进行POS标注和依存分析(使用goeswith对子词进行处理)的DeBERTa(V2)模型,基于 deberta-base-thai 进行了预训练。
class UDgoeswith(object): def __init__(self,bert): from transformers import AutoTokenizer,AutoModelForTokenClassification self.tokenizer=AutoTokenizer.from_pretrained(bert) self.model=AutoModelForTokenClassification.from_pretrained(bert) def __call__(self,text): import numpy,torch,ufal.chu_liu_edmonds w=self.tokenizer(text,return_offsets_mapping=True) v=w["input_ids"] x=[v[0:i]+[self.tokenizer.mask_token_id]+v[i+1:]+[j] for i,j in enumerate(v[1:-1],1)] with torch.no_grad(): e=self.model(input_ids=torch.tensor(x)).logits.numpy()[:,1:-2,:] r=[1 if i==0 else -1 if j.endswith("|root") else 0 for i,j in sorted(self.model.config.id2label.items())] e+=numpy.where(numpy.add.outer(numpy.identity(e.shape[0]),r)==0,0,numpy.nan) g=self.model.config.label2id["X|_|goeswith"] r=numpy.tri(e.shape[0]) for i in range(e.shape[0]): for j in range(i+2,e.shape[1]): r[i,j]=r[i,j-1] if numpy.nanargmax(e[i,j-1])==g else 1 e[:,:,g]+=numpy.where(r==0,0,numpy.nan) m=numpy.full((e.shape[0]+1,e.shape[1]+1),numpy.nan) m[1:,1:]=numpy.nanmax(e,axis=2).transpose() p=numpy.zeros(m.shape) p[1:,1:]=numpy.nanargmax(e,axis=2).transpose() for i in range(1,m.shape[0]): m[i,0],m[i,i],p[i,0]=m[i,i],numpy.nan,p[i,i] h=ufal.chu_liu_edmonds.chu_liu_edmonds(m)[0] if [0 for i in h if i==0]!=[0]: m[:,0]+=numpy.where(m[:,0]==numpy.nanmax(m[[i for i,j in enumerate(h) if j==0],0]),0,numpy.nan) m[[i for i,j in enumerate(h) if j==0]]+=[0 if i==0 or j==0 else numpy.nan for i,j in enumerate(h)] h=ufal.chu_liu_edmonds.chu_liu_edmonds(m)[0] u="# text = "+text+"\n" v=[(s,e) for s,e in w["offset_mapping"] if s<e] for i,(s,e) in enumerate(v,1): q=self.model.config.id2label[p[i,h[i]]].split("|") u+="\t".join([str(i),text[s:e],"_",q[0],"_","|".join(q[1:-1]),str(h[i]),q[-1],"_","_" if i<len(v) and e<v[i][0] else "SpaceAfter=No"])+"\n" return u+"\n" nlp=UDgoeswith("KoichiYasuoka/deberta-base-thai-ud-goeswith") print(nlp("หลายหัวดีกว่าหัวเดียว"))
使用 ufal.chu-liu-edmonds .Or不使用ufal.chu-liu-edmonds:
from transformers import pipeline nlp=pipeline("universal-dependencies","KoichiYasuoka/deberta-base-thai-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple") print(nlp("หลายหัวดีกว่าหัวเดียว"))