{"id":28306816,"url":"https://github.com/applied-machine-learning-lab/llm4msr","last_synced_at":"2026-01-24T09:33:24.766Z","repository":{"id":258539101,"uuid":"874131054","full_name":"Applied-Machine-Learning-Lab/LLM4MSR","owner":"Applied-Machine-Learning-Lab","description":null,"archived":false,"fork":false,"pushed_at":"2024-11-19T04:08:58.000Z","size":11225,"stargazers_count":6,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-20T04:38:16.674Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Applied-Machine-Learning-Lab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-10-17T09:57:51.000Z","updated_at":"2025-06-08T10:44:41.000Z","dependencies_parsed_at":"2024-10-20T13:31:25.199Z","dependency_job_id":null,"html_url":"https://github.com/Applied-Machine-Learning-Lab/LLM4MSR","commit_stats":null,"previous_names":["applied-machine-learning-lab/llm4msr"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Applied-Machine-Learning-Lab/LLM4MSR","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Applied-Machine-Learning-Lab%2FLLM4MSR","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Applied-Machine-Learning-Lab%2FLLM4MSR/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Applied-Machine-Learning-Lab%2FLLM4MSR/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Applied-Machine-Learning-Lab%2FLLM4MSR/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Applied-Machine-Learning-Lab","download_url":"https://codeload.github.com/Applied-Machine-Learning-Lab/LLM4MSR/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Applied-Machine-Learning-Lab%2FLLM4MSR/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28723235,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-24T08:27:05.734Z","status":"ssl_error","status_checked_at":"2026-01-24T08:27:01.197Z","response_time":89,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-05-24T04:12:46.107Z","updated_at":"2026-01-24T09:33:24.761Z","avatar_url":"https://github.com/Applied-Machine-Learning-Lab.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# LLM4MSR: An Effective Efficient Interpretable LLM-Enhanced Paradigm for Multi-Scenario Recommendation\n\nThe implement code of LLM4MSR. Take **STAR** as backbone model and **Amazon** dataset as the illustration example.\n\n**Preparation**\n\n1. Install requirement packages of [ChatGLM2-6B](https://huggingface.co/THUDM/chatglm2-6b) by running:\n\n\n    **'pip install protobuf transformers==4.30.2 cpm_kernels torch\u003e=2.0 gradio mdtex2html sentencepiece accelerate'**\n\n\n2. Download the [ChatGLM2-6B](https://huggingface.co/THUDM/chatglm2-6b) model from hugging face and test by running the demo on it.\n\n3. Modify the original source code of function of sample(beam=1) in 'lib/python3.9/site-packages/transformers/generation/utils' to output the last hidden state in order to get rid of **cuda out of memory** error.\n\n4. Combine the file 'amazon_user_prompt_part_1.csv' and 'amazon_user_prompt_part_2.csv' into 'amazon_user_prompt.csv' in dataset folder.\n\n\n**Step 1: Multi-Scenario Knowledge Reasoning**\n\n  Run the code 'produce_llm_dict_domain.py' and 'produce_llm_dict_user.py', which take about **\u003c2 days** for all the 24752 users on single GPU.\n\n**Step 2: Multi-Level Knowledge Fusion**\n\n  Run the following command:\n\n  **'python multi_amazon.py'**\n\n  and you can see the AUC and Logloss results on all scenarios (**Remember** to search for the learning rate, which is sensitive).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fapplied-machine-learning-lab%2Fllm4msr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fapplied-machine-learning-lab%2Fllm4msr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fapplied-machine-learning-lab%2Fllm4msr/lists"}