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---
license: mit
language:
- fr
library_name: transformers
tags:
- linformer
- legal
- medical
- RoBERTa
- pytorch
---
# Jargon-general-base
[Jargon](https://hal.science/hal-04535557/file/FB2_domaines_specialises_LREC_COLING24.pdf) is an efficient transformer encoder LM for French, combining the LinFormer attention mechanism with the RoBERTa model architecture.
Jargon is available in several versions with different context sizes and types of pre-training corpora.
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## Using Jargon models with HuggingFace transformers
You can get started with `jargon-general-base` using the code snippet below:
```python
from transformers import AutoModelForMaskedLM, AutoTokenizer, pipeline
tokenizer = AutoTokenizer.from_pretrained("PantagrueLLM/jargon-general-base", trust_remote_code=True)
model = AutoModelForMaskedLM.from_pretrained("PantagrueLLM/jargon-general-base", trust_remote_code=True)
jargon_maskfiller = pipeline("fill-mask", model=model, tokenizer=tokenizer)
output = jargon_maskfiller("Il est allé au <mask> hier")
```
- **Funded by**
- GENCI-IDRIS (Grant 2022 A0131013801)
- French National Research Agency: Pantagruel grant ANR-23-IAS1-0001
- MIAI@Grenoble Alpes ANR-19-P3IA-0003
- PROPICTO ANR-20-CE93-0005
- Lawbot ANR-20-CE38-0013
- Swiss National Science Foundation (grant PROPICTO N°197864)
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- **Language(s):** French
- **License:** MIT
- **Developed by:** Vincent Segonne
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