Fill-Mask
Transformers
Safetensors
pakmosaic
pakistan
multilingual
encoder
research-preview
sota-target
custom_code
Instructions to use ProximaAI/PakMosaic-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProximaAI/PakMosaic-Small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ProximaAI/PakMosaic-Small", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("ProximaAI/PakMosaic-Small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from ProximaAI/PakMosaic-Small: direct link, hf CLI and curl.
- Browser
- Download file 1.45 kB
-
https://huggingface.co/ProximaAI/PakMosaic-Small/resolve/main/README.md
- Command line
-
hf download hf://ProximaAI/PakMosaic-Small/README.md
-
curl -L -o README.md https://huggingface.co/ProximaAI/PakMosaic-Small/resolve/main/README.md
1.45 kB
metadata
library_name: transformers
license: apache-2.0
pipeline_tag: fill-mask
language:
- ur
- ps
- pa
- sd
- skr
- ks
- gu
tags:
- pakmosaic
- pakistan
- multilingual
- encoder
- research-preview
- sota-target
- fill-mask
PakMosaic-Small
This is the finished ~67M PakMosaic encoder after a 2B-token serious train on the clean scale mix.
Architecture
Encoder-only MLM: pre-norm, RoPE, GeGLU, full attention, tied embeddings.
| hidden size | 512 |
| layers | 12 |
| heads | 8 |
| intermediate | 2048 |
| vocab | 32,000 |
How to load
from transformers import AutoModelForMaskedLM, AutoTokenizer, pipeline
repo = "ProximaAI/PakMosaic-Small"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForMaskedLM.from_pretrained(repo, trust_remote_code=True)
fill = pipeline("fill-mask", model=model, tokenizer=tok)
print(fill("یہ ایک <mask> ہے۔"))
AutoModel also works (trust_remote_code=True) and returns encoder hidden states.
Data
Training mix is Wikimedia plus third-party web crawls used under their original terms. Only Wikimedia / CC BY-SA is redistributed on the Hub: PakMosaic-Wikimedia-v0.2.
Citation
Acknowledgements
Wikipedia volunteer editors, native reviewers, and Proxima AI.