artindnr / ChatBerry-1

🍰 ChatBerry-1

ChatBerry-1 is a fine-tuned version of artindnr/strawberry-1 , converted from a reasoning ("thinking") model into a direct-answer chat model . Reasoning traces are disabled — ChatBerry-1 responds directly, without emitting a separate chain-of-thought / analysis channel, making it faster and simpler to deploy for everyday conversational use in Farsi, English, and other languages.

Model Details

• Base model: artindnr/strawberry-1 (itself fine-tuned from openai/gpt-oss-20b , 21B parameters)
• Architecture: gpt_oss
• Fine-tuned by: artindnr
• License: Apache 2.0
• Languages: Farsi (Persian), English, and multilingual support
• Model type: Causal decoder-only chat language model (reasoning disabled)

What's New

Strawberry-1 was built to generate high-quality Farsi reasoning traces. ChatBerry-1 takes the opposite approach: it strips reasoning out of the loop entirely, so the model:

• Answers directly, without producing an analysis (chain-of-thought) channel
• Behaves like a standard instruction-tuned chat model rather than a "thinking" model
• Retains Strawberry-1's Farsi and multilingual fluency, now applied to direct conversational responses
• Is better suited for latency-sensitive or simpler chat use cases where reasoning traces aren't needed

How to Use

ChatBerry-1 uses the gpt-oss chat template (Harmony format) shipped with the base model, so it works with 🤗 Transformers.

Installation

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:

Generation

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

MODEL_ID = "artindnr/chatberry-1"

tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForCausalLM.from_pretrained(
    MODEL_ID,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

USER_PROMPT = "تو کی هستی و اسمت چیه؟"

messages = [
    {"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][inputs["input_ids"].shape[-1]:], skip_special_tokens=True))

Unlike Strawberry-1, there's no need to set a reasoning language system message or parse out separate analysis / final channels — ChatBerry-1 goes straight to its final answer in the final channel, so decoding just the newly generated tokens with skip_special_tokens=True gives you the plain-text response directly.

Intended Use

ChatBerry-1 is intended for:

• General-purpose Farsi and multilingual chat assistants
• Applications where direct, low-latency responses are preferred over visible reasoning traces
• Research comparing reasoning vs. non-reasoning fine-tunes of the same base model

Limitations

• ChatBerry-1 trades away Strawberry-1's explicit chain-of-thought reasoning; for tasks that benefit from visible step-by-step reasoning, artindnr/strawberry-1 may be a better fit.
• As with any fine-tune, ChatBerry-1 inherits the general capabilities and limitations of the gpt-oss-20b base model and the strawberry-1 checkpoint it was built from, including the possibility of hallucinated facts.
• No formal safety fine-tuning beyond what is inherited from the base model and Strawberry-1 has been applied; use appropriate safeguards in production settings.

License

This model is released under the Apache 2.0 license, consistent with the base gpt-oss-20b model and strawberry-1 .

Citation

If you use ChatBerry-1 in your work, please cite:

@misc{chatberry1,
  title  = {ChatBerry-1: A Direct-Answer Chat Fine-tune of Strawberry-1},
  author = {artindnr},
  year   = {2026},
  url    = {https://huggingface.co/artindnr/chatberry-1}
}

Acknowledgements

Built on top of artindnr/strawberry-1 , itself fine-tuned from openai/gpt-oss-20b