| from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline | |
| # Global variables to cache model and tokenizer | |
| model = None | |
| tokenizer = None | |
| nlp = None | |
| def init(): | |
| global model, tokenizer, nlp | |
| model_name_or_path = "." | |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path) | |
| tokenizer = AutoTokenizer.from_pretrained(model_name_or_path) | |
| nlp = pipeline("text2text-generation", model=model, tokenizer=tokenizer) | |
| def inference(payload): | |
| inputs = payload.get("inputs", "") | |
| if not inputs: | |
| return {"error": "No inputs provided"} | |
| # Run generation pipeline | |
| outputs = nlp(inputs, max_length=256) | |
| return outputs | |
Xet Storage Details
- Size:
- 672 Bytes
- Xet hash:
- 3acd52afbf30bffab02805a02023d35f5532be265361a2e2e19e6b180cacfcdd
·
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