Instructions to use ChenyuEcho/fine_tuned_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ChenyuEcho/fine_tuned_model with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("ChenyuEcho/fine_tuned_model")

sentences = [
    "What are the exact start and end times for overnight on-site IT coverage during the maintenance window?",
    "Subject: Issue Encountered with Insurance Verification Workflow\nFrom: Julian R. Torres\nTo: Rachel K. Martinez\nDate: 2025-10-20\n\nHi Rachel,\n\nI wanted to flag an ongoing issue with the insurance verification process that’s impacting our ED admissions, especially during peak hours. Sometimes, patient insurance details aren’t fully updated in the system, and it’s causing delays getting clearance from registration. Could we discuss ways to streamline the info handoff between the ED and registration, or is there a protocol update I might’ve missed? Any suggestions or insight from your end would be appreciated.\n\nThanks,\nJulian",
    "Subject: EHR Medication Documentation Concerns – Joint Commission Survey Preparation\nFrom: Katherine M. Walsh\nTo: Angela R. Scott\nDate: 2025-10-20\n\nHello Angela,\n\nAs we continue our preparations for the upcoming Joint Commission survey, I have identified a recurring issue with the EHR medication documentation process. Specifically, the current workflow does not require entry of medication batch numbers or precise dose changes during intraoperative adjustments, which is inconsistent with recent Joint Commission medication safety protocols. This gap could potentially lead to survey citations and, more importantly, compromises our ability to track medication safety accurately. Could you assist in reviewing and, if possible, updating the EHR fields so that batch numbers and intraoperative dose modifications are mandatory entries? If you need additional clinical detail, I am happy to collaborate.\n\nThank you for your attention to this patient safety concern.\n\nBest regards,\nKatherine",
    "Subject: Re: Scheduled System Maintenance Downtime – Main Hospital & Outpatient Clinics\nFrom: Richard T. Howard\nTo: David R. Park\nDate: 2025-10-16\n\nHi David,\n\nThank you for your prompt reply and for raising the question about tech support coverage during the maintenance window. I can confirm that our IT team will have on-site personnel available overnight to assist with any urgent issues that arise, particularly for clinical teams. Please feel free to direct your staff to extension 4471 if immediate support is required during downtime.\n\nLet me know if you need any additional details or have further concerns.\n\nBest,\nRichard"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Notebooks
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Kaggle

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