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--- |
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language: |
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- code |
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license: apache-2.0 |
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tags: |
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- code |
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- gpt2 |
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- generation |
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datasets: |
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- "codeparrot/github-code-clean" |
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- "openai_humaneval" |
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metrics: |
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- "evaluate-metric/code_eval" |
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--- |
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# CodeParrot-Multi 🦜 (small) |
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CodeParrot-Multi 🦜 is a GPT-2 model (110M parameters) trained to generate code in 9 programming languages: "Java", "JavaScript", "PHP", "Python", "C#", "C++", "GO", "Ruby" and "TypeScript". |
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## Usage |
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You can load the CodeParrot-Multi model and tokenizer directly in `transformers`: |
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```Python |
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from transformers import AutoTokenizer, AutoModelWithLMHead |
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tokenizer = AutoTokenizer.from_pretrained("codeparrot/codeparrot-small-multi") |
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model = AutoModelWithLMHead.from_pretrained("codeparrot/codeparrot-small-multi") |
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inputs = tokenizer("def hello_world():", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
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or with a `pipeline`: |
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```Python |
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from transformers import pipeline |
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pipe = pipeline("text-generation", model="codeparrot/codeparrot-small-multi") |
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outputs = pipe("def hello_world():") |
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``` |
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## Training |
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The model was trained on the small [Github code small](https://huggingface.co/datasets/loubnabnl/github-small-near-dedup) after near deduplication, a subset of [Github code dataset](https://huggingface.co/datasets/codeparrot/github-code-clean) with the following settings: |
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|Config|Value| |
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|-------|-----| |
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|Batch size| 192 | |
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|Context size| 1024 | |
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|Training steps| 300'000| |
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|Gradient accumulation| 2| |
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|Gradient checkpointing| False| |
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|Learning rate| 5e-4 | |
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|Weight decay | 0.1 | |
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|Warmup steps| 2000 | |
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|Schedule| Cosine | |
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The training was executed on 16 x A100 (40GB) GPUs. This setting amounts to roughly 58 billion tokens. |
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## Performance |
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We evaluated the model on OpenAI's [HumanEval](https://huggingface.co/datasets/openai_humaneval) benchmark which consists of programming challenges: |
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| Metric | Value | |
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|-------|-----| |
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|pass@1 | --% | |
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|pass@10 | --% | |
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|pass@100 | --% | |
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The [pass@k metric](https://huggingface.co/metrics/code_eval) tells the probability that at least one out of k generations passes the tests. |
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## Resources |
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- Code: [repository](https://github.com/huggingface/transformers/tree/master/examples/research_projects/codeparrot) |
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