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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

NEED AI - Category Recommendation

Fine-tuned T5 model for categorizing user service requests into predefined categories.

Model Details

  • Base Model: google/flan-t5-base
  • Task: Text2Text Generation
  • Fine-tuned for: NEED Service Marketplace Platform
  • Language: English
  • License: MIT

Usage

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
# or AutoModelForSequenceClassification for moderation
# or SentenceTransformer for semantic-search

model_name = "yogami9/need-category-recommendation"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

# Example usage
input_text = "Your input here"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(result)

Training Data

Trained on curated datasets specific to the NEED platform's service categories and user interactions.

Limitations

  • Optimized for English language
  • Best performance on NEED platform-specific queries
  • May require fine-tuning for other domains

Contact

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