Translation
Transformers
Safetensors
English
Turkish
qwen3
text-generation
Generated from Trainer
unsloth
sft
trl
text-generation-inference
Instructions to use Ba2han/muon-translation-prototype with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ba2han/muon-translation-prototype with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Ba2han/muon-translation-prototype")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Ba2han/muon-translation-prototype") model = AutoModelForCausalLM.from_pretrained("Ba2han/muon-translation-prototype") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Ba2han/muon-translation-prototype with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Ba2han/muon-translation-prototype to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Ba2han/muon-translation-prototype to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Ba2han/muon-translation-prototype to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Ba2han/muon-translation-prototype", max_seq_length=2048, )
Model Card for m-tr-1
This model is a fine-tuned version of Ba2han/test-model-muon.
This is a TR<>EN translation prototype. It makes a lot of mistakes.
Quick start
from transformers import pipeline
generator = pipeline(
"text-generation",
model="Ba2han/muon-translation-prototype",
device="cuda"
)
messages = [
{"role": "system", "content": ""},
{"role": "user", "content": "British Shorthair, dünyanın en popüler kedi ırklarından biridir."},
]
output = generator(
messages,
max_new_tokens=64,
temperature=0.1,
min_p=0.1,
top_k=10,
repetition_penalty=1.05,
do_sample=True,
return_full_text=False
)[0]
print(output["generated_text"])
The British shorthair is one of the most popular breeds in the world.
Training procedure
This model was trained with SFT.
Framework versions
- TRL: 0.23.0
- Transformers: 4.56.2
- Pytorch: 2.8.0
- Datasets: 4.3.0
- Tokenizers: 0.22.1
Citations
Cite TRL as:
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
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