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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: apache-2.0
+datasets:
+- open-r1/codeforces-cots
+language:
+- en
+base_model: open-r1/OlympicCoder-32B
+pipeline_tag: text-generation
+---
+
+AWQ quantization: done by stelterlab in INT4 GEMM with AutoAWQ by casper-hansen (https://github.com/casper-hansen/AutoAWQ/)
+
+Original Weights by the open-r1 team. Original Model Card follows:
+
+# Model Card for OlympicCoder-32B
+
+OlympicCoder-32B is a code mode that achieves very strong performance on competitive coding benchmarks such as LiveCodeBench andthe 2024 International Olympiad in Informatics.
+
+## Model description
+
+- **Model type:** A 32B parameter model fine-tuned on a decontaminated version of the codeforces dataset.
+- **Language(s) (NLP):** Primarily English
+- **License:** apache-2.0
+- **Finetuned from model:** [Qwen/Qwen2.5-Coder-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct)
+
+## Evaluation
+
+![](./ioi-evals.png)
+
+
+
+
+## Usage
+Here's how you can run the model using the `pipeline()` function from 🤗 Transformers:
+
+```python
+# pip install transformers
+# pip install accelerate
+
+import torch
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="open-r1/OlympicCoder-32B", torch_dtype=torch.bfloat16, device_map="auto")
+
+# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
+messages = [
+    {"role": "user", "content": "Write a python program to calculate the 10th Fibonacci number"},
+]
+prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+outputs = pipe(prompt, max_new_tokens=8000, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+#<|im_start|>user
+#Write a python program to calculate the 10th fibonacci number<|im_end|>
+#<|im_start|>assistant
+#<think>Okay, I need to write a Python program that calculates the 10th Fibonacci number. Hmm, the Fibonacci sequence starts with 0 and 1. Each subsequent number is the sum of the two preceding ones. So the sequence goes: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, and so on. ...
+```
+
+
+## Training procedure
+### Training hyper-parameters
+
+The following hyperparameters were used during training on 16 H100 nodes:
+
+- dataset: open-r1/codeforces-cots_decontaminated
+- learning_rate: 4.0e-5
+- train_batch_size: 1
+- seed: 42
+- packing: false
+- distributed_type: fsdp
+- num_devices: 128
+- gradient_accumulation_steps: 1
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine_with_min_lr
+- min_lr_rate: 0.1
+- lr_scheduler_warmup_ratio: 0.03
+- num_epochs: 10.0
+

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config.json

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+    "quant_method": "awq",
+    "version": "gemm",
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generation_config.json

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