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bart-base-aslg-gloss

425GMM / bart-base-aslg-gloss

Run on huggingface.co
huggingface.co
Total runs: 182
24-hour runs: -6
7-day runs: -30
30-day runs: -235
Model's Last Updated: September 09 2026
text-generation

Introduction of bart-base-aslg-gloss

Model Details of bart-base-aslg-gloss

BART-base fine-tuned for English -> ASL gloss (ASLG-PC12)

facebook/bart-base fine-tuned on the training split of the ASLG-PC12 English-ASL gloss parallel corpus. Input is a lowercased English sentence; output is an upper-case ASL gloss sequence in the corpus's conventions ( X- pronouns, DESC- modifiers).

This model is one of the systems in a small project comparing grammar-constrained decoding (xgrammar) with unconstrained decoding for gloss generation. Code, grammars and evaluation scripts: https://github.com/TheRealGioviok/asl-gloss-nlp

Training
Base model facebook/bart-base
Data training split of the Kaggle redistribution of ASLG-PC12 (87,710 pairs, no official split; deduplicated and re-split 80/10/10 with seed 42 in the project)
Epochs 3
Effective batch size 32
Learning rate 3e-5
Max length 128 tokens (source and target)
Steps 6,084

Weights are stored in fp16 (the evaluation in the project also ran in fp16).

Results (1,000-sentence test sample, greedy decoding)
Decoding BLEU chrF Exact match Sequence validity
Unconstrained 76.7 93.3 44.5% 48.6%
Constrained (grammar v3) 73.2 85.9 42.8% 100%
Constrained + copy rule (v3) 74.1 86.3 44.5% 100%

"Sequence validity" is the share of outputs whose every token is in the closed gloss vocabulary.

Usage 
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

repo = "425GMM/bart-base-aslg-gloss"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForSeq2SeqLM.from_pretrained(repo)

src = "we should behave outside european waters in just the same way as we do at home ."
ids = tok(src, return_tensors="pt")
out = model.generate(**ids, max_new_tokens=128)
print(tok.decode(out[0], skip_special_tokens=True))

Source sentences in ASLG-PC12 are lowercased with spaces before punctuation; feed the model text in the same form.

Limitations

ASLG-PC12 glosses are rule-generated from Europarl text, not produced by signers. The model learns those rules; it is not a general English-to-ASL translator and scores do not transfer to human-annotated gloss corpora.

Runs of 425GMM bart-base-aslg-gloss on huggingface.co

182
Total runs
-6
24-hour runs
-16
3-day runs
-30
7-day runs
-235
30-day runs

More Information About bart-base-aslg-gloss huggingface.co Model

More bart-base-aslg-gloss license Visit here:

https://choosealicense.com/licenses/apache-2.0

bart-base-aslg-gloss huggingface.co

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bart-base-aslg-gloss huggingface.co Url

https://huggingface.co/425GMM/bart-base-aslg-gloss

425GMM bart-base-aslg-gloss online free

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https://huggingface.co/425GMM/bart-base-aslg-gloss

bart-base-aslg-gloss install

bart-base-aslg-gloss is an open source model from GitHub that offers a free installation service, and any user can find bart-base-aslg-gloss on GitHub to install. At the same time, huggingface.co provides the effect of bart-base-aslg-gloss install, users can directly use bart-base-aslg-gloss installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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https://huggingface.co/425GMM/bart-base-aslg-gloss

Url of bart-base-aslg-gloss

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Provider of bart-base-aslg-gloss huggingface.co

425GMM
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huggingface.co

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