How to use from
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 AlekseyCalvin/Lyrical_MT_ru2en_2c_Gemma3n_e4b_orpo_r32_adapter 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 AlekseyCalvin/Lyrical_MT_ru2en_2c_Gemma3n_e4b_orpo_r32_adapter to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AlekseyCalvin/Lyrical_MT_ru2en_2c_Gemma3n_e4b_orpo_r32_adapter to start chatting
Load model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="AlekseyCalvin/Lyrical_MT_ru2en_2c_Gemma3n_e4b_orpo_r32_adapter",
    max_seq_length=2048,
)
Quick Links

LYRICAL Russian to English Machine Translation Model

Variant 0.23a: ORPO-tuned Gemma3n-E4B-Instruct Rank32 Adapter

  • Developed by: SilverAgePoets.com
  • Model type: [Lyrical Machine Translation]
  • Languages (NLP): [Совпоюзный, Worldish] aka [Russian, English]
  • Finetuned from: [unsloth/gemma-3n-e4b-it-unsloth-bnb-4bit]

Experimental WIP prototype Rank 32/Alpha 32 adapter for Gemma3n-E4B-Instruct base model.
This adapter belongs to our Lyrical MT (Machine Translation) series of fine-tuned LLMs and adapters.
Our ultimate aim with the Lyrical MT project is to iteratively foster a translation model capable of adaptively localizing idiomatic, formal/poetic/rhythmic, and performance-catered features of lyrical input texts, whilst retaining adequate accuracy at the level of direct semantic translation.

USES:

Intended scope of effective applicability limited to:
Russian to English translation of song lyrics, poems, scriptures, slogans, etc...
Translation from a Russian-language input text structured in accordance with literary, aesthetic, or/and vocalization-catering compositional devices to an English output text exhibiting cross-lingually rebalanced approximations of source-matched formal features.

Depending on the relative performance, foundations, and the idiosyncracies of a given checkpoint/adapter variant in the Lyrical MT series, the above-suggested applicability scope may plausibly extend to:
Russian to English text-to-text translation in general.
English to Russian translation.

The Lyrical MT models were fine-tuned primarily on single-line (fragment), double-line (couplet), quadruple-line (quatrain), and full-length bilingual textual inputs.

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