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| Use a pipeline as a high-level helper | |
| from transformers import pipeline | |
| pipe = pipeline("fill-mask", model="casehold/custom-legalbert") | |
| # Load model directly | |
| from transformers import AutoModel | |
| model = AutoModel.from_pretrained("casehold/custom-legalbert") | |
| import requests | |
| API_URL = "https://api-inference.huggingface.co/models/casehold/custom-legalbert" | |
| headers = {"Authorization": "Bearer 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"} | |
| def query(payload): | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| return response.json() | |
| output = query({ | |
| "inputs": "The answer to the universe is [MASK].", | |
| }) | |
| import gradio as gr | |
| gr.Interface.load("models/casehold/custom-legalbert").launch() |