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View details ↗Leanstral-1.5-119B-A6B-GGUF
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View details ↗A finetuned model designed to recognize and classify Personally Identifiable Information (PII) within unstructured text data. This powerful model accurately identifies a wide range of PII categories, such as account names, credit card numbers, emails, phone numbers, and addresses. The model is specifically trained to detect various PII types, including but not limited to: The PII Identifier Model ensures data privacy and compliance by effectively detecting and categorizing sensitive information within documents, emails, user-generated content, and more. Make your data processing safer and more secure with our state-of-the-art PII detection technology.
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View details ↗Florence-2-base
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Adjust provider, category or input/output filters. New models are added continuously.
COST EXPLORER
Great models. Clear costs.
Adjust monthly token usage to compare estimated API costs.
1 M = 1 million tokens · USD
Compares base text-token rates within the same channel
Compares base text-token rates within the same channel
Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.
MODEL HANDBOOK
Understand before you choose
How should API prices be compared?+
Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.
Do open weights mean free commercial use?+
Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.
Is the top-ranked model the best for me?+
Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.