Edit model card

training logs

install

usage

import torch
from flash import FLASHForMaskedLM
from transformers import BertTokenizerFast
tokenizer = BertTokenizerFast.from_pretrained("junnyu/flash_small_wwm_cluecorpussmall")
model = FLASHForMaskedLM.from_pretrained("junnyu/flash_small_wwm_cluecorpussmall")
model.eval()
text = "天气预报说今天的天[MASK]很好,那么我[MASK]一起去公园玩吧!"
inputs = tokenizer(text, return_tensors="pt", padding="max_length", max_length=512,  return_token_type_ids=False) #这里必须是512,不然结果可能不对。
with torch.no_grad():
    pt_outputs = model(**inputs).logits[0]

pt_outputs_sentence = "pytorch: "
for i, id in enumerate(tokenizer.encode(text)):
    if id == tokenizer.mask_token_id:
        val,idx = pt_outputs[i].softmax(-1).topk(k=5)
        tokens = tokenizer.convert_ids_to_tokens(idx)
        new_tokens = []
        for v,t in zip(val.cpu(),tokens):
            new_tokens.append(f"{t}+{round(v.item(),4)}")
        pt_outputs_sentence += "[" + "||".join(new_tokens) + "]"
    else:
        pt_outputs_sentence += "".join(
            tokenizer.convert_ids_to_tokens([id], skip_special_tokens=True))
print(pt_outputs_sentence)
# pytorch: 天气预报说今天的天[气+0.994||天+0.0015||空+0.0014||晴+0.0005||阳+0.0003]很好,那么我[们+0.9563||就+0.0381||也+0.0032||俩+0.0004||来+0.0002]一起去公园玩吧!
Downloads last month
3
Inference Examples
Inference API (serverless) has been turned off for this model.