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artindnr/strawberry-1.1
strawberry-1.1 is a text generation model from artindnr. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
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Downloads · 30 days
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From the Hugging Face model README

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.
gpt_ossStrawberry-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:
Strawberry-1.1 was produced by further fine-tuning artindnr/strawberry-1 on a hybrid English-Persian dataset.
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.
Strawberry-1.1 uses the gpt-oss chat template (Harmony format) inherited from the base model, so it works with 🤗 Transformers.
pip install torch --index-url https://download.pytorch.org/whl/cu128
pip install "trl>=0.20.0" "peft>=0.17.0" "transformers>=4.55.0" "kernels>=0.12.0"
This has been verified to work with:
| Package | Version |
|---|---|
torch | 2.8.0+cu129 |
transformers | 5.14.1 |
trl | 1.9.2 |
peft | 0.20.0 |
accelerate | 1.10.1 |
tokenizers | 0.22.0 |
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
MODEL_ID = "artindnr/strawberry-1.1"
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForCausalLM.from_pretrained(
MODEL_ID,
torch_dtype=torch.bfloat16,
device_map="auto",
)
REASONING_LANGUAGE = "English" # e.g. "English", "Farsi", "Persian"
SYSTEM_PROMPT = f"reasoning language: {REASONING_LANGUAGE}"
USER_PROMPT = "تو کی هستی و اسمت چیه؟"
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": USER_PROMPT},
]
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(
**inputs,
max_new_tokens=512,
temperature=0.6,
do_sample=True,
)
print(tokenizer.decode(outputs[0]))
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.
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.
Strawberry-1.1 is intended for:
strawberry-1 and gpt-oss-20b base models, including the possibility of hallucinated facts and reasoning errors.This model is released under the Apache 2.0 license, consistent with the base strawberry-1 and gpt-oss-20b models.
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}
}
Built on top of artindnr/strawberry-1 and, in turn, openai/gpt-oss-20b, using the Thinking Datasets collection.