StephanAkkerman/FinTwitBERT-sentiment

Classification · served with Text Embeddings Inference · ↓ 128.1K downloads a month · View on Hugging Face

Weights: 220 MB
GPU memory needed: about 1.8 GB
Model allows: 512 tokens
Memory · disk: 8 GB · 21 GB
Architecture: BertForSequenceClassification
Licence: mit

Hardware and deploy

Deploying embedding and reranking models (Text Embeddings Inference) is coming soon.

Prices are per hour for the whole machine and its disk, right now. Speed is Vast's DLPerf score of the machine, relative to the cheapest. Best value: the most speed per dollar. Only machines with a Vast reliability above 95% that download at 400 Mbit/s or more are offered: the machine fetches the model itself.

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