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This model was converted to GGUF format from [`open-thoughts/OpenThinker-32B`](https://huggingface.co/open-thoughts/OpenThinker-32B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/open-thoughts/OpenThinker-32B) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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This model was converted to GGUF format from [`open-thoughts/OpenThinker-32B`](https://huggingface.co/open-thoughts/OpenThinker-32B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/open-thoughts/OpenThinker-32B) for more details on the model.
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This model is a fine-tuned version of Qwen/Qwen2.5-32B-Instruct on the OpenThoughts-114k dataset.
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The dataset is derived by distilling DeepSeek-R1 using the data pipeline available on github. More info about the dataset can be found on the dataset card at OpenThoughts-114k dataset.
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Intended uses & limitations
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Apache 2.0 License
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Training procedure
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We finetune Qwen2.5-32B-Instruct on OpenThoughts-114k for 3 epochs with a 16k context length using LlamaFactory. Our full training configuration is provided in our repository. Training the 32B model on OpenThoughts-114k was done on AWS SageMaker with 8xH100 P5 nodes. On 4 nodes, this took around 90 hours. Meanwhile, for training on OpenThoughts-Unverified-173k, we used 96 nodes of 4xA100 (64 GB per GPU), training took 30 hours, spending 11,520 A100 hours on the Leonardo Supercomputer.
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---
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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