YAML Metadata Warning: The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
from transformers import T5ForConditionalGeneration
from transformers import T5TokenizerFast as T5Tokenizer
import pandas as pd
model = "svjack/comet-atomic-zh"
device = "cpu"
#device = "cuda:0"
tokenizer = T5Tokenizer.from_pretrained(model)
model = T5ForConditionalGeneration.from_pretrained(model).to(device).eval()

NEED_PREFIX = '以下事件有哪些必要的先决条件:'
EFFECT_PREFIX = '下面的事件发生后可能会发生什么:'
INTENT_PREFIX = '以下事件的动机是什么:'
REACT_PREFIX = '以下事件发生后,你有什么感觉:'

event = "X吃了一顿美餐。"
for prefix in [NEED_PREFIX, EFFECT_PREFIX, INTENT_PREFIX, REACT_PREFIX]:
    prompt = "{}{}".format(prefix, event)
    encode = tokenizer(prompt, return_tensors='pt').to(device)
    answer = model.generate(encode.input_ids,
                           max_length = 128,
        num_beams=2,
        top_p = 0.95,
        top_k = 50,
        repetition_penalty = 2.5,
        length_penalty=1.0,
        early_stopping=True,
                           )[0]
    decoded = tokenizer.decode(answer, skip_special_tokens=True)
    print(prompt, "\n---答案:", decoded, "----\n")

以下事件有哪些必要的先决条件:X吃了一顿美餐。 
---答案: X买了食物 ----

下面的事件发生后可能会发生什么:X吃了一顿美餐。 
---答案: X会吃到好的食物 ----

以下事件的动机是什么:X吃了一顿美餐。 
---答案: X想吃东西 ----

以下事件发生后,你有什么感觉:X吃了一顿美餐。 
---答案: X的味道很好 ----
Downloads last month
5
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Spaces using svjack/comet-atomic-zh 2