Strawberry-1.1
is a fine-tuned version of
artindnr/strawberry-1
, further trained on a hybrid English-Persian dataset to strengthen
dual-linguality reasoning
— the model's ability to reason fluently in English and Farsi at once, without the two languages interfering with each other mid-thought.
Languages:
Farsi (Persian), English, and multilingual reasoning support
Model type:
Causal decoder-only language model with reasoning ("thinking") traces
What's New
Strawberry-1 was the first ~20B-class open model to produce high-quality Farsi reasoning traces, but it could run into
language conflict
: when a prompt pulled on both English and Farsi at once, its reasoning could become inconsistent or unstable as the two languages competed within the same trace.
Strawberry-1.1 was fine-tuned specifically to resolve this. Relative to Strawberry-1, it:
Reasons across English and Farsi
within the same trace without the languages conflicting
, where Strawberry-1 would show that conflict
Preserves the reasoning-language control and general instruction-following ability inherited from Strawberry-1
Builds on the same Harmony chat template and usage pattern as Strawberry-1, so it's a drop-in upgrade
Training
Strawberry-1.1 was produced by further fine-tuning
artindnr/strawberry-1
on a hybrid English-Persian dataset.
Training Data
Strawberry-1.1 was trained on a hybrid English-Persian dataset drawn from the
Thinking Datasets
collection, the same collection used to train the base Strawberry-1 model.
How to Use
Strawberry-1.1 uses the
gpt-oss
chat template (Harmony format) inherited from the base model, so it works with 🤗 Transformers.
This prints the full Harmony-formatted output, including the
analysis
(reasoning) and
final
(answer) channels and their special tokens. To get just the plain-text final answer, decode with
skip_special_tokens=True
and parse out the
final
channel, or use
tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:], skip_special_tokens=True)
to only decode the newly generated tokens.
Reasoning in a specific language
Set
reasoning language: <Language>
as the
system
message content to control the language of the reasoning trace (the
analysis
channel), independent of the language the user writes in. For example, setting
REASONING_LANGUAGE = "Farsi"
will produce a Farsi reasoning trace even for a prompt in another language. Strawberry-1.1's fine-tuning specifically targeted keeping this stable when a prompt draws on both languages at once.
Note that the model's default chat template also auto-populates a Harmony-format preamble (identity, knowledge cutoff, current date, reasoning effort, valid channels) ahead of your system/developer message — you don't need to set these yourself.
Intended Use
Strawberry-1.1 is intended for:
Research and experimentation on multilingual and Farsi-language reasoning, particularly cross-lingual (English-Farsi) reasoning
Building Farsi-language assistants, tutoring tools, and reasoning-heavy applications
Farsi reasoning quality, while a focus of this fine-tune, may still occasionally mix in English tokens or phrasing, especially for highly technical topics.
As with any fine-tune, Strawberry-1.1 inherits the general capabilities and limitations of the
strawberry-1
and
gpt-oss-20b
base models, including the possibility of hallucinated facts and reasoning errors.
No formal safety fine-tuning beyond what is inherited from the base models has been applied; use appropriate safeguards in production settings.
License
This model is released under the
Apache 2.0
license, consistent with the base
strawberry-1
and
gpt-oss-20b
models.
Citation
If you use Strawberry-1.1 in your work, please cite:
@misc{strawberry11,
title = {Strawberry-1.1: Resolving English-Farsi Reasoning Conflict in a Fine-tuned GPT-OSS-20B Model},
author = {artindnr},
year = {2026},
url = {https://huggingface.co/artindnr/strawberry-1.1}
}
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