--- title: "model_card vs Large-Language-Model-Notebooks-Course" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bigscience-workshop-model-card-vs-peremartra-large-language-model-notebooks-course" tools: ["bigscience-workshop-model-card", "peremartra-large-language-model-notebooks-course"] --- # model_card vs Large-Language-Model-Notebooks-Course *GraphCanon updated Sep 20, 2026* ## Verdict Pick model_card if the model_card for BLOOM LM provides comprehensive details on the development, training data, risks, and evaluation of a large, multilingual language model. It is useful for researchers and developers working with multil; pick Large-Language-Model-Notebooks-Course if a developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. [model_card](https://github.com/bigscience-workshop/model_card) reports 25 GitHub stars, 5 forks, and 0 open issues, last pushed Jul 11, 2022. [Large-Language-Model-Notebooks-Course](https://medium.com/@peremartra/list/large-language-models-practical-course-66b4ce5943ce) has 1.8k stars, 450 forks, and 0 open issues, last pushed May 28, 2026. Figures are from public GitHub metadata via [model_card's repository](https://github.com/bigscience-workshop/model_card) and [Large-Language-Model-Notebooks-Course's repository](https://github.com/peremartra/Large-Language-Model-Notebooks-Course). | | [model_card](/tools/bigscience-workshop-model-card.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Tagline | Model Card for BLOOM LM | Practical course about Large Language Models | | Stars | 25 | 1,824 | | Forks | 5 | 450 | | Open issues | 0 | 0 | | Language | - | Jupyter Notebook | | Adopt for | The model_card for BLOOM LM provides comprehensive details on the development, training data, risks, and evaluation of a large, multilingual language model. It is useful for researchers and developers working with multil | A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. | | Persona | - | - | | Runtime | - | - | | License | The model card is licensed under the Apache-2.0 license, allowing for broad use and modification with attribution. | MIT | | Categories | Evaluation & Observability, LLM Frameworks | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [model_card](/tools/bigscience-workshop-model-card.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 1529d | 114d | | Stars delta | -1 (30d) | +3 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/bigscience-workshop-model-card/trust.md) | [trust report](/tools/peremartra-large-language-model-notebooks-course/trust.md) | ## Decision facts: model_card - **Requirements:** The model card is intended for use with the BLOOM language model and provides details on its architecture, training data, and evaluation.; It is recommended to refer to the BLOOM model card for comprehensive information before using the model in any application. - **Adopt for:** The model_card for BLOOM LM provides comprehensive details on the development, training data, risks, and evaluation of a large, multilingual language model. It is useful for researchers and developers working with multil - **License detail:** The model card is licensed under the Apache-2.0 license, allowing for broad use and modification with attribution. ## Decision facts: Large-Language-Model-Notebooks-Course - **Adopt for:** A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. ## Choose when ### Choose model_card if… - License: model_card is Apache-2.0, Large-Language-Model-Notebooks-Course is MIT. - Requirements: The model card is intended for use with the BLOOM language model and provides details on its architecture, training data, and evaluation.; It is recommended to refer to the BLOOM model card for comprehensive information before using the model in any application.. - Tags unique to model_card: bigscience, bloom, language-model, model card. - When you need detailed information on the development and training of BLOOM, a large multilingual language model. ### Choose Large-Language-Model-Notebooks-Course if… - License: Large-Language-Model-Notebooks-Course is MIT, model_card is Apache-2.0. - Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain. - Also covers Inference & Serving, Model Training. - You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ## When NOT to use model_card - If you are looking for a model card for a different language model, as this card is specific to BLOOM. - When you need real-time updates or interactive features, as the model card is static and does not provide dynamic information. - If you require a model card for a proprietary or closed-source model, as BLOOM is an open-access model. - When you need a model card that includes specific use cases or applications beyond the general information provided. ## When NOT to use Large-Language-Model-Notebooks-Course - Seeking a complete, finalized course where all content is available for immediate use without future updates. - Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ## Common questions ### What is the difference between model_card and Large-Language-Model-Notebooks-Course? model_card: Model Card for BLOOM LM. Large-Language-Model-Notebooks-Course: Practical course about Large Language Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose model_card over Large-Language-Model-Notebooks-Course? Choose model_card over Large-Language-Model-Notebooks-Course when License: model_card is Apache-2.0, Large-Language-Model-Notebooks-Course is MIT; Requirements: The model card is intended for use with the BLOOM language model and provides details on its architecture, training data, and evaluation.; It is recommended to refer to the BLOOM model card for comprehensive information before using the model in any application.; Tags unique to model_card: bigscience, bloom, language-model, model card; When you need detailed information on the development and training of BLOOM, a large multilingual language model. ### When should I choose Large-Language-Model-Notebooks-Course over model_card? Choose Large-Language-Model-Notebooks-Course over model_card when License: Large-Language-Model-Notebooks-Course is MIT, model_card is Apache-2.0; Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain; Also covers Inference & Serving, Model Training; You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ### When should I avoid model_card? If you are looking for a model card for a different language model, as this card is specific to BLOOM. When you need real-time updates or interactive features, as the model card is static and does not provide dynamic information. If you require a model card for a proprietary or closed-source model, as BLOOM is an open-access model. When you need a model card that includes specific use cases or applications beyond the general information provided. ### When should I avoid Large-Language-Model-Notebooks-Course? Seeking a complete, finalized course where all content is available for immediate use without future updates. Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ### Is model_card or Large-Language-Model-Notebooks-Course more popular on GitHub? Large-Language-Model-Notebooks-Course has more GitHub stars (1,824 vs 25). Stars measure visibility, not whether either tool fits your constraints. ### Are model_card and Large-Language-Model-Notebooks-Course open source? Yes - both are open-source projects on GitHub (model_card: Apache-2.0, Large-Language-Model-Notebooks-Course: MIT). ### Where can I find alternatives to model_card or Large-Language-Model-Notebooks-Course? GraphCanon lists graph-backed alternatives at [model_card alternatives](/tools/bigscience-workshop-model-card/alternatives) and [Large-Language-Model-Notebooks-Course alternatives](/tools/peremartra-large-language-model-notebooks-course/alternatives) ([model_card markdown twin](/tools/bigscience-workshop-model-card/alternatives.md), [Large-Language-Model-Notebooks-Course markdown twin](/tools/peremartra-large-language-model-notebooks-course/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/bigscience-workshop-model-card-vs-peremartra-large-language-model-notebooks-course.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, model_card or Large-Language-Model-Notebooks-Course? model_card: Dormant. Large-Language-Model-Notebooks-Course: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for model_card and Large-Language-Model-Notebooks-Course? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [model_card trust report](/tools/bigscience-workshop-model-card/trust); [Large-Language-Model-Notebooks-Course trust report](/tools/peremartra-large-language-model-notebooks-course/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bigscience-workshop-model-card`](/api/graphcanon/graph?tool=bigscience-workshop-model-card) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_