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artindnr/strawberry-1, converted from a reasoning ("thinking") model into a direct-answer chat model. Reasoning traces are disabled — ChatBerry-1.1 responds directly, without emitting a separate chain-of-thought / analysis channel. This release scales up training data ~4x over ChatBerry-1, resulting in improved response quality and consistency.gpt_ossartindnr/strawberry-1 on an expanded version of the direct chat-style (non-reasoning) SFT data used for ChatBerry-1 — roughly 4x the number of training examples. As with ChatBerry-1, this SFT pass overrides Strawberry-1's reasoning behavior, teaching the model to skip the analysis channel and go straight to a final answer.gpt-oss chat template (Harmony format) shipped with the base model, so it works with 🤗 Transformers.1pip install torch --index-url https://download.pytorch.org/whl/cu128
2pip install "trl>=0.20.0" "peft>=0.17.0" "transformers>=4.55.0" "kernels>=0.12.0"| 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 |
1import torch
2from transformers import AutoModelForCausalLM, AutoTokenizer
3
4MODEL_ID = "artindnr/chatberry-1.1"
5
6tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
7model = AutoModelForCausalLM.from_pretrained(
8 MODEL_ID,
9 torch_dtype=torch.bfloat16,
10 device_map="auto",
11)
12
13USER_PROMPT = "تو کی هستی و اسمت چیه؟"
14
15messages = [
16 {"role": "user", "content": USER_PROMPT},
17]
18
19inputs = tokenizer.apply_chat_template(
20 messages,
21 add_generation_prompt=True,
22 tokenize=True,
23 return_dict=True,
24 return_tensors="pt",
25).to(model.device)
26
27outputs = model.generate(
28 **inputs,
29 max_new_tokens=512,
30 temperature=0.6,
31 do_sample=True,
32)
33
34print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:], skip_special_tokens=True))reasoning language system message or parse out separate analysis / final channels — ChatBerry-1.1 goes straight to its final answer, so decoding just the newly generated tokens with skip_special_tokens=True gives you the plain-text response directly.artindnr/strawberry-1 may be a better fit.gpt-oss-20b base model and the strawberry-1 checkpoint it was built from, including the possibility of hallucinated facts.gpt-oss-20b model and strawberry-1.1@misc{chatberry11,
2 title = {ChatBerry-1.1: A Direct-Answer Chat Fine-tune of Strawberry-1},
3 author = {artindnr},
4 year = {2026},
5 url = {https://huggingface.co/artindnr/chatberry-1.1}
6}artindnr/strawberry-1, itself fine-tuned from openai/gpt-oss-20b.