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README.md
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- **Developed by:** Deci
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- **Model type:** DeciCoder-6B is an auto-regressive language model based on the transformer decoder architecture, using variable Grouped Query Attention.
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- **Language(s):** Python, Java, JavaScript, Rust, C++, C, C#
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- **License:** Model checkpoints are licensed under the [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
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## Documentation
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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checkpoint = "Deci/DeciCoder-
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device = "cuda" # for GPU usage or "cpu" for CPU usage
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tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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- **Developed by:** Deci
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- **Model type:** DeciCoder-6B is an auto-regressive language model based on the transformer decoder architecture, using variable Grouped Query Attention.
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- **Language(s):** Python, Java, JavaScript, Rust, C++, C, C#, Go
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- **License:** Model checkpoints are licensed under the [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
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## Documentation
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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checkpoint = "Deci/DeciCoder-6B"
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device = "cuda" # for GPU usage or "cpu" for CPU usage
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tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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