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Model: GaMS-Beta/GaMS-9B-SFT-Translator
Source: Original Platform
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---
license: gemma
language:
- sl
- en
base_model:
- cjvt/GaMS-9B-Instruct
pipeline_tag: text-generation
---
# Model Card for GaMS-9B-SFT-Translator
GaMS-9B-SFT-Trasnlator represents the version of GaMS-9B-Instruct further trained using SFT on approximately 130k English to Slovene translation pairs.
![image/png](https://cdn-uploads.huggingface.co/production/uploads/652d40a78fa1fbb0aae165bb/94gX0PG8zRB_Zg31K2y_i.png)
## Acknowledgment
The model was developed within the [PoVeJMo](https://www.cjvt.si/povejmo/en/project/) research program (Adaptive Natural Language Processing with Large Language Models), particularly within the research project titled SloLLaMai -- Open-access computationally efficient models for Slovenian. The program is funded within the Recovery and Resilience Plan by the Slovenian Research and Innovation Agency (ARIS) and NextGenerationEU. The authors also acknowledge the financial support from the Slovenian Research and Innovation Agency (research core funding No. P6-0411 -- Language Resources and Technologies for Slovene).
## Usage
The model can be run through `pipeline` API using the following code:
```python
from transformers import pipeline
model_id = "GaMS-Beta/GaMS-9B-SFT-Translator"
pline = pipeline(
"text-generation",
model=model_id,
device_map="cuda" # replace with "mps" to run on a Mac device
)
# Example of response generation
text_to_translate = "A fast brown fox jumped over the lazy dog."
message = [{"role": "user", "content": f"Prevedi naslednje besedilo v slovenščino.\n{text_to_translate}"}]
response = pline(message, max_new_tokens=512)
print("Slovene translation:", response[0]["generated_text"][-1]["content"])
```
For multi GPU inference set the `device_map` to `auto`: