fasttext-language-identification vs Bangla-twoclass-Sentiment-Analyzer
Specs, VRAM requirements and download trends — updated 10 November 2026.
facebook · A · Open weights
Params
—
Context
—
30d
830 K
cc-by-nc-4.0 · non-commercial
Arunavaonly · B · Open weights
Params
280 M
Context
512
30d
3.4 M
mit · commercial OK
Specification comparison
Differences are highlighted; identical values are muted.
| Specification | fasttext-language-identification | Bangla-twoclass-Sentiment-Analyzer |
|---|---|---|
| Parameters | — | 280 M |
| Architecture | — | XLMRobertaForSequenceClassification |
| Context length | — | 512 |
| Licence | cc-by-nc-4.0 | mit |
| Commercial use | Not allowed | Allowed |
| Languages | — | — |
| Downloads 30d | 830,390 | 3,368,929 |
| Downloads all time | 186.4 M | 7.5 M |
| Quantizations on the Hub | — | SAFETENSORS |
| Gated | No | No |
| First seen on the Hub | 2023-03-06 | 2023-09-03 |
Download trend
Daily snapshots, last 90 days (13 Aug – 10 Nov)
3.4 M260 K
fasttext-language-identification
Bangla-twoclass-Sentiment-Analyzer
VRAM side by side
On RTX 4090 · 24 GB · 8K context unless noted
Bangla-twoclass-Sentiment-Analyzer · fp16
1.8 GB / 24 GB
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