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, 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

Uses

It is shit model....

import openvino_genai as ov_genai
from openvino_genai import GenerationConfig
import huggingface_hub as hf_hub

hf_hub.snapshot_download("hsuwill000/Llama-3.1-TAIDE-LX-8B-Chat_int4_ov", local_dir="ov")

pipe = ov_genai.LLMPipeline("ov", "CPU")
tokenizer = pipe.get_tokenizer()
tokenizer.set_chat_template(tokenizer.chat_template)

config = GenerationConfig(
    stop_strings=set(["<|eot_id|>"])  # ✅ 這是 set
)
#, "<|end_header_id|>"


output_buffer = ""

def streamer(subword):
    global output_buffer
    output_buffer += subword
    print(subword, end='', flush=True)


pipe.start_chat()
while True:
    try:
        question = input('question:\n')
        
        # 手動構建 prompt(模仿 ChatML 或 LLaMA 3 instruct 風格)
        prompt = (
            "<|user|>\n" + question + "\n<|eot_id|>"
        )      
    except EOFError:
        break

    output_buffer = ""  # 清空累積 buffer
    pipe.generate(prompt, streamer=streamer, max_new_tokens=4096, config=config)
    print('\n----------\n')
pipe.finish_chat()
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