FacebookAI / text-classification updated 2 years ago

roberta-large-mnli

Name: roberta-large-mnli
Author: FacebookAI

- Model Details - How To Get Started With the Model - Uses - Risks, Limitations and Biases - Training - Evaluation - Environmental Impact - Technical Specifications - Citation Information - Model Card Authors

Params

360 M

Context

512

Downloads 30d

291 K

Likes

213

Commercial use: allowed mit Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

297 K278 K

Jul 28Jul 31Aug 3Aug 6

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	f32	1.4 GB	2.1 GB	✅ Runs comfortably

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Specifications

Architecture: RobertaForSequenceClassification
Parameters: 360 M
Tensor type: F32
Context length: 512
Vocabulary: 50,265
Layers / heads: 24 / 16
Licence: mit
First seen on the Hub: 2022-03-02
Training datasets: multi_nli, wikipedia, bookcorpus
Added to our catalog: 2026-07-28

Compare with

bge-reranker-v2-m3 19.2 M finbert 5.6 M bge-reranker-base 4.6 M Prompt-Guard-86M 4.5 M twitter-roberta-base-sentiment-latest 2.6 M bertweet-base-sentiment-analysis 1.5 M

Appears in

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