Comments (4)
We’ll release some smaller versions of StarCoder in a few weeks
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okay,Thank you for your work!
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Although we filtered for Python/Java/JS files there might be some C/C++ code in those files that the model learned. You can refer to this paper for some details about language spillover
Language models are able to generate code with correct syntax and pass unit tests in programming languages they are not intentionally trained on. We hypothesize that the data “spillover” effect, where code in one language is present in other languages through code comments or co-occurrences. Such amount of “spillover” data are enough for large language models to learn different languages that are embedded within the main language.
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Thank you very much for your response. Additionally, I would like to ask if you have any other pre-trained models for C or C++ code besides StarCoder.
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Related Issues (19)
- weird behavior when setting batch_size HOT 2
- no_fp16 ? HOT 2
- Finetuning on multiple language HOT 2
- DeepSpeed Integration HOT 2
- Linked Colab isn't working
- Issue running inference on Huggingface after model upload HOT 2
- Question (not issue) related to dataset generation HOT 2
- I used multiple GPUs for training, but there were the following errors. How can I solve them? HOT 1
- Cuda OOM even with batch size 1 and lower seq length on 16GB GPU HOT 3
- I only generated three files after fine-tuning, is it correct? Why is there no tokenizer.json file? HOT 1
- Why is the inference speed using fp16 or bf16 similar to fp32? HOT 1
- moving a fine tuned model to gpt_bigcode HOT 2
- Can I use it to fine tune bigcode/starcoderplus? HOT 1
- Formatting FIM data HOT 1
- ValueError: Batch does not contain any data (`None`). At the end of all iterable data available before expected stop iteration. HOT 2
- Ways to reproduce this approach HOT 2
- How to inference the model HOT 1
- FIM Evaluation
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