JSR-0003/Computer-Science_All-Courses-Guru
0
1---2license: llama43datasets:4- ComputerScienceHouse/GroceryInContext5- Lots-of-LoRAs/task701_mmmlu_answer_generation_high_school_computer_science6- AyoubChLin/ARxiv_Metadata_ComputerScience7- 5CD-AI/Viet-ComputerScience-VQA8- shibarashii/general-computer-science-queries9- Kaeyze/computer-science-synthetic-dataset10- Danhpham2000/computer_science_qa_dataset11- masoudc/mmlu-college-computer-science-compilers12- masoudc/mmlu-college-computer-science-distribution-parallelism13- Lots-of-LoRAs/task688_mmmlu_answer_generation_college_computer_science14- >-15 DataoceanAI/University-level_Mathematics_Physics_Chemistry_Computer_Science_Reasoning_Corpus16- SukrutAI/Computer-Science-Parallel-Dataset-Indic17- SukrutAI/Computer-Science-Conversational-Dataset-Indic18- herronej/SciTrust2-ComputerScienceQA19- anonymous-paper-author/original_mmlu_pro_computerscience20- >-21 anonymous-paper-author/anonymous-paper-author_reproduction_o4mini_computerscience22- >-23 anonymous-paper-author/anonymous-paper-author_reproduction_deepseekr1_computerscience24- >-25 anonymous-paper-author/anonymous-paper-author_reproduction_g3_mini_computerscience26- >-27 anonymous-paper-author/anonymous-paper-author_reproduction_qwen235b_computerscience28- Jenjamin3000/RAG_documents_computer_science29- cristiano-sartori/college_computer_science30- cristiano-sartori/high_school_computer_science31- gabrieljimenez/wikipedia-english-handpicked-computer-science32- gabrieljimenez/epfl-computer-science-mcqa33- japan-ai-official/jmmlu-curated-computer-science34- paperlantern/computer_science_ai_search_queries35- paperlantern/computer_science_non_ai_search_queries36- joey234/mmlu-college_computer_science-neg37- joey234/mmlu-high_school_computer_science-neg38- joey234/mmlu-college_computer_science-neg-prepend39- joey234/mmlu-high_school_computer_science-neg-prepend40- joey234/mmlu-college_computer_science-verbal-neg-prepend41- joey234/mmlu-high_school_computer_science-verbal-neg-prepend42- joey234/mmlu-college_computer_science-rule-neg-prepend43- joey234/mmlu-high_school_computer_science-rule-neg-prepend44- joey234/mmlu-college_computer_science-original-neg45- joey234/mmlu-high_school_computer_science-original-neg46- joey234/mmlu-college_computer_science-original-neg-prepend47- joey234/mmlu-high_school_computer_science-original-neg-prepend48- joey234/mmlu-college_computer_science-neg-answer49- joey234/mmlu-high_school_computer_science-neg-answer50- joey234/mmlu-college_computer_science51- joey234/mmlu-high_school_computer_science-dev52- awsebbas/QA_computer_science53- joey234/mmlu-college_computer_science-neg-prepend-fix54- joey234/mmlu-high_school_computer_science-neg-prepend-fix55- joey234/mmlu-college_computer_science-neg-prepend-verbal56- brucewlee1/mmlu-high-school-computer-science57- brucewlee1/mmlu-college-computer-science58- samehuss/Computersciencewords59- barath13/computerscience9160- Puidii/aalen_university_faculty_computer_science61- AlaaElhilo/Wikipedia_ComputerScience62language:63- en64base_model:65- meta-llama/Llama-4-Scout-17B-16E-Instruct66- meta-llama/Llama-4-Maverick-17B-128E-Instruct67- unsloth/Llama-4-Scout-17B-16E-Instruct-GGUF68- meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP869- meta-llama/Llama-4-Scout-17B-16E70metrics:71- accuracy72- f173- exact_match74- bleu75library_name: transformers76tags:77- Llama-478- transformer79- text-generation80- code-generation81- c++82- computer-science83- educational84- visual-studio85- open-source86- student-assistant87model-index:88- name: CS-AI-LLaMA4-Assistant89 results:90 - task:91 type: question-answering92 name: QA (Computer Science)93 dataset:94 name: Multiple CS QA Sets95 type: multiple96 metrics:97 - type: accuracy98 value: 0.0499 - type: f1100 value: 0.07101 - type: exact_match102 value: 0.76103 - task:104 type: text-generation105 name: C++ Code Generation106 dataset:107 name: Combined code datasets108 type: code109 metrics:110 - type: codebleu111 value: 0.73112new_version: JSR-0003/Computer-Science_All-Courses-Guru113---114 115# CS-AI-LLaMA4-Assistant116 117A fine-tuned LLaMA 4 model designed as a study and code generation assistant for undergraduate Computer Science students...118---119# Model Card for Model ID120 121<!-- Provide a quick summary of what the model is/does. -->122 123This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).124 125## Model Details126 127### Model Description128 129<!-- Provide a longer summary of what this model is. -->130 131 132 133- **Developed by:** [More Information Needed]134- **Funded by [optional]:** [More Information Needed]135- **Shared by [optional]:** [More Information Needed]136- **Model type:** [More Information Needed]137- **Language(s) (NLP):** [More Information Needed]138- **License:** [More Information Needed]139- **Finetuned from model [optional]:** [More Information Needed]140 141### Model Sources [optional]142 143<!-- Provide the basic links for the model. -->144 145- **Repository:** [More Information Needed]146- **Paper [optional]:** [More Information Needed]147- **Demo [optional]:** [More Information Needed]148 149## Uses150 151<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->152 153### Direct Use154 155<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->156 157[More Information Needed]158 159### Downstream Use [optional]160 161<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->162 163[More Information Needed]164 165### Out-of-Scope Use166 167<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->168 169[More Information Needed]170 171## Bias, Risks, and Limitations172 173<!-- This section is meant to convey both technical and sociotechnical limitations. -->174 175[More Information Needed]176 177### Recommendations178 179<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->180 181Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.182 183## How to Get Started with the Model184 185Use the code below to get started with the model.186 187[More Information Needed]188 189## Training Details190 191### Training Data192 193<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->194 195[More Information Needed]196 197### Training Procedure198 199<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->200 201#### Preprocessing [optional]202 203[More Information Needed]204 205 206#### Training Hyperparameters207 208- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->209 210#### Speeds, Sizes, Times [optional]211 212<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->213 214[More Information Needed]215 216## Evaluation217 218<!-- This section describes the evaluation protocols and provides the results. -->219 220### Testing Data, Factors & Metrics221 222#### Testing Data223 224<!-- This should link to a Dataset Card if possible. -->225 226[More Information Needed]227 228#### Factors229 230<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->231 232[More Information Needed]233 234#### Metrics235 236<!-- These are the evaluation metrics being used, ideally with a description of why. -->237 238[More Information Needed]239 240### Results241 242[More Information Needed]243 244#### Summary245 246 247 248## Model Examination [optional]249 250<!-- Relevant interpretability work for the model goes here -->251 252[More Information Needed]253 254## Environmental Impact255 256<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->257 258Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).259 260- **Hardware Type:** [More Information Needed]261- **Hours used:** [More Information Needed]262- **Cloud Provider:** [More Information Needed]263- **Compute Region:** [More Information Needed]264- **Carbon Emitted:** [More Information Needed]265 266## Technical Specifications [optional]267 268### Model Architecture and Objective269 270[More Information Needed]271 272### Compute Infrastructure273 274[More Information Needed]275 276#### Hardware277 278[More Information Needed]279 280#### Software281 282[More Information Needed]283 284## Citation [optional]285 286<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->287 288**BibTeX:**289 290[More Information Needed]291 292**APA:**293 294[More Information Needed]295 296## Glossary [optional]297 298<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->299 300[More Information Needed]301 302## More Information [optional]303 304[More Information Needed]305 306## Model Card Authors [optional]307 308[More Information Needed]309 310## Model Card Contact311 312[More Information Needed]