Sentence Similarity
sentence-transformers
Safetensors
qwen3
feature-extraction
dense
Generated from Trainer
dataset_size:816
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use ChenyuEcho/corruption_emaillevel_newtrainmethod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ChenyuEcho/corruption_emaillevel_newtrainmethod with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ChenyuEcho/corruption_emaillevel_newtrainmethod") sentences = [ "Search for evidence of regulators requesting clarification on barrel aging logs for NOM-006-SCFI-2012 certification for batches 3124-A and 3125-B.", "Subject: Exciting News: New Distribution Agreement Expands Our North American Reach\nDate: 2025-08-06T16:41:00\nFrom: Thomas Tom Bradford\nParticipants: Sarah Mitchell; Kevin O'Brien; Patricia Reeves\n\nBody:\nDear Executive Team,\n\nI am pleased to announce that Agave Spirits International has finalized a new distribution agreement with Pacific Spirits Group, targeting the U.S. West Coast and Canadian markets. This partnership is expected to increase our premium product presence by at least 35% over the next fiscal year, with flagship brands such as Tequila Oro and Sierra Azul leading the portfolio. This strategic move positions us for accelerated growth and strengthens our competitive advantage in crucial markets.\n\nI will share further details during our leadership call next week. In the meantime, please begin preparing your teams to support the anticipated rollout in Q3. Your collaboration is vital to ensuring a successful launch.\n\nThank you for your continued commitment and leadership.\n\nBest regards,\nTom", "Subject: Re: Inventory Discrepancy at Tequila Distillery – Proposal to Resolve\nDate: 2025-11-21T10:30:00\nFrom: Roberto Garza\nParticipants: Carlos Delgado\n\nBody:\nHola Carlos,\n\nThank you for flagging this and for approaching it thoughtfully. I completely agree that a recount with Pedro’s team is the right step—showing transparency is key. Mañana at 10am works for me. Before we meet, could you or Pedro please pull the detailed transfer logs from the last quarter? Having those on hand will help clarify if this is a timing or recording issue. As you said, it’s likely just a minor oversight, but it's best we review all angles.\n\nLooking forward to resolving this together with cafecito—appreciate the care you both put into these matters.\n\nSaludos,\nRoberto", "Subject: Quality Certification Requirements for Recent Batches – Clarification Needed\nDate: 2025-12-01T06:07:00\nFrom: Carlos Delgado\nParticipants: Roberto Garza\n\nBody:\nHola Roberto,\n\nHope you're having a good afternoon. I wanted to touch base regarding the NOM-006-SCFI-2012 certification process for our most recent lots (especially Batch 3124-A and 3125-B). While the initial chromatographic analyses were within threshold, there were minor variances in the ester content and methanol limits. Nothing fuera de lo común, pero los reguladores have requested clarification on our barrel aging logs for these particular batches. You know, in Mexico, relationships matter, and sometimes a simple phone call or una pequeña cena can resolve these technicalities. This is how business is done here, and I’m confident our local practices meet the spirit and letter of the regulations.\n\nLet’s ensure the technical team keeps detailed test result documentation (including los controles de temperatura y humedad en la bodega). If you need my support defending our methodology, I’m happy to take the lead—nuestro equipo es lo más importante. Please advise if you need me to coordinate with external auditors or if a site visit would be beneficial.\n\nUn abrazo,\nCarlos\n\n--\nCarlos Delgado\nCountry Manager, Mexico Operations\nAgave Spirits International\nTequila, Jalisco" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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