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Model: bigatuna/Qwen3-1.7B-Sushi-Coder
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-1.7B
+datasets:
+  - ericholam/codeforces-sft-dataset-beta
+  - TeichAI/claude-4.5-opus-high-reasoning-250x
+language:
+  - en
+tags:
+  - code
+  - reasoning
+  - competitive-programming
+  - sft
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# Qwen3-1.7B-Sushi-Coder
+
+A fine-tuned Qwen3-1.7B model optimized for code generation and competitive programming.
+
+## Model Details
+
+- **Base Model:** [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B)
+- **Fine-tuning Method:** SFT with LoRA (merged)
+- **Training Steps:** 1000
+- **Context Length:** 2048
+
+## Training
+
+This model was fine-tuned using:
+- **LoRA** (r=8, alpha=16) on attention and MLP layers
+- **Liger Kernel** for memory efficiency
+- **Packing** with FlashAttention-2
+- **Cosine learning rate schedule** (2e-5 peak)
+
+### Datasets
+
+- [ericholam/codeforces-sft-dataset-beta](https://huggingface.co/datasets/ericholam/codeforces-sft-dataset-beta) - 1408 competitive programming examples
+- [TeichAI/claude-4.5-opus-high-reasoning-250x](https://huggingface.co/datasets/TeichAI/claude-4.5-opus-high-reasoning-250x) - High-quality reasoning examples
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "bigatuna/Qwen3-1.7B-Sushi-Coder",
+    torch_dtype="auto",
+    device_map="auto",
+    trust_remote_code=True,
+)
+tokenizer = AutoTokenizer.from_pretrained("bigatuna/Qwen3-1.7B-Sushi-Coder")
+
+messages = [
+    {"role": "user", "content": "Write a Python function to solve the two-sum problem."}
+]
+
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.6, top_p=0.95, top_k=20)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Sampling Parameters
+
+For best results with Qwen3 models:
+- **Temperature:** 0.6-0.7
+- **Top-p:** 0.95
+- **Top-k:** 20
+- **Do not use greedy decoding** (temp=0 causes repetitions)
+
+## License
+
+Apache 2.0