huggingface/tokenizers

3 other commands the scanner could not classify

Commands from CI steps and task runners that look like checks but match no known tool. Some are checks, some are not.

• cargo semver-checks --package tokenizers
• hf download hf-internal-testing/tokenizers-test-data gpt2.json albert-base-v1-tokenizer.json --repo-type dataset --re...
• twine check --strict dist/*

full scan as JSON

• Return results not panicsLibraries should never panic as this can crash applications using the library. Always return a `Result` type rather than using functions ...

  huggingface/tokenizers Error Handling Rust ml-systems 2023-11-14

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• Simplify for readabilityPrioritize code readability by using simpler and more direct expressions. When possible, return values directly instead of using temporar...

  huggingface/tokenizers Code Style Rust ml-systems 2022-02-14

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• Handle nullable types idiomaticallyUse Rust's idiomatic patterns when working with Option and Result types\ \ to prevent panics and improve code clarity. \n\n**Avoid unwrap...

  huggingface/tokenizers Null Handling Rust ml-systems 2024-06-10

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• Minimize memory allocationsAvoid unnecessary memory allocations to improve performance. Each allocation has both CPU and memory overhead that can accumulate signifi...

  huggingface/tokenizers Performance Optimization Rust ml-systems 2023-11-14

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• Prefer explicit API designWhen designing APIs, favor simple and explicit interfaces over flexible but complex ones. This reduces cognitive load, improves compile-t...

  huggingface/tokenizers API Rust ml-systems 2025-03-24

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• Choose semantically clear identifiersSelect parameter and method names that accurately describe their purpose and behavior, avoiding ambiguous terms that can lead to confusio...

  huggingface/tokenizers Naming Conventions Rust ml-systems 2023-11-14

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• Choose optimal data structuresSelect data structures based on their algorithmic complexity and usage patterns. Consider the tradeoffs between different structures (e.g...

  huggingface/tokenizers Algorithms Rust ml-systems 2020-10-23

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• Optimize workflow triggersConfigure CI workflows with targeted triggers and path filters to balance thoroughness with efficiency. Run critical build jobs on every ...

  huggingface/tokenizers CI/CD Yaml ml-systems 2024-10-17

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• Modular model componentsDesign machine learning model code with clear component boundaries and proper separation of concerns. Each component (tokenizer, normaliz...

  huggingface/tokenizers AI Rust ml-systems 2024-07-11

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• Manage version constraintsWhen configuring dependency version constraints in project files, follow these principles: 1. Be explicit about version ranges to balance...

  huggingface/tokenizers Configurations Toml ml-systems 2023-10-02

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• Thread-safe resource sharingWhen sharing mutable data between threads, use the `Arc>` pattern to ensure thread safety. `Arc` provides thread-safe reference...

  huggingface/tokenizers Concurrency Rust ml-systems 2022-03-10

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• Pythonic API designDesign APIs that follow Python language conventions and idioms rather than blindly mirroring the underlying implementation language. Cons...

  huggingface/tokenizers API Python ml-systems 2020-11-11

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• Purpose-indicating descriptive namesChoose names for variables, methods, parameters, and fixtures that clearly communicate their purpose, content, and behavior. Names should...

  huggingface/tokenizers Naming Conventions Python ml-systems 2020-10-13

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• Test algorithmic behaviorWhen testing algorithms, verify their actual functionality rather than just checking for proper instantiation or property modification. E...

  huggingface/tokenizers Algorithms Python ml-systems 2025-01-21

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• Version AI dependencies appropriatelyWhen adding or updating dependencies for AI/ML libraries in your project, follow these two key practices: 1. **Set appropriate version co...

  huggingface/tokenizers AI Toml ml-systems 2024-06-07

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• Smart configuration defaultsPrefer smart configuration defaults that auto-detect the environment instead of requiring explicit configuration flags. When possible, im...

  huggingface/tokenizers Configurations Python ml-systems 2024-03-30

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• Prioritize tokenizer simplicityWhen implementing AI model components like tokenizers, favor simplicity over rarely-used features that significantly increase code comple...

  huggingface/tokenizers AI TypeScript ml-systems 2023-05-17

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• Use explicit assertionsTests should assert specific expected values rather than just verifying general functionality. This practice makes tests more robust agai...

  huggingface/tokenizers Testing Rust ml-systems 2023-05-06

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• Flexible tokenizer implementationWhen implementing tokenizers for AI models, ensure flexibility and robust behavior across different contexts: 1. Initialize tokenizers wi...

  huggingface/tokenizers AI Python ml-systems 2022-12-26

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• Robust workflow configurationsEnsure CI/CD workflow configuration files follow best practices for maintainability and correctness: 1. Use centralized dependency manage...

  huggingface/tokenizers Configurations Yaml ml-systems 2022-10-05

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• Consistent API designWhen designing and modifying APIs, ensure consistency in parameter naming, default values, and which functionality is exposed. Each API d...

  huggingface/tokenizers API Other ml-systems 2021-12-15

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• Document for comprehensionAdd comprehensive documentation that helps others understand both the interface and implementation of your code. This includes: 1. **Deta...

  huggingface/tokenizers Documentation Python ml-systems 2021-07-21

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• Avoid unsafe codePrioritize memory safety and security over performance optimizations by avoiding unsafe code blocks, especially in libraries. Even when b...

  huggingface/tokenizers Security Rust ml-systems 2021-12-06

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