# Tools > Every listed resource, editors’ picks first. The filters below can be combined. - Search: append `?q=` to the URL. Separate several keywords with spaces; all of them must match. Matches name, repository, tags, professions, description and README. - Filter by type: append `?type=` to the URL. - Filter by profession: append `?profession=` to the URL. Separate several ids with commas; a resource matches when it suits any of them. Ids are listed at https://hebbmind.com/api/v1/professions - Filter by tag: append `?tag=` to the URL. Separate several tags with commas; a resource must carry all of them. Tags are listed at https://hebbmind.com/api/v1/tags Resources for Full-stack / Indie or ML / AI, Tagged `vllm`: 3 items. > - Full-stack / Indie: General software work: coding-agent workflows, code review, debugging and Git collaboration. > - ML / AI: Model training, evaluation and LLM application development. - [vLLM](https://hebbmind.com/cli/vllm.md): [CLI] High-throughput LLM inference and serving engine: vllm serve starts an OpenAI- and Anthropic-compatible server in one command. Supports 200+ model architectures from Hugging Face, quantization and distributed inference. Aimed mainly at NVIDIA, AMD and other GPUs. - [AI Research Skills](https://hebbmind.com/skill/ai-research-skills.md): [Skill] Nearly 100 skills spanning the AI research workflow: ideation and literature review, fine-tuning and post-training, distributed training, inference serving, evaluation, interpretability and paper writing, tied together by an autoresearch orchestration skill. - [AI Research Skills](https://hebbmind.com/plugin/ai-research-skills.md): [Plugin] Plugin marketplace for AI research with nearly 100 skills in 23 categories, from ideation, fine-tuning and post-training to distributed training, inference serving, evaluation and paper writing, coordinated end to end by the autoresearch skill.