VectorSpaceLab

Routes CenterNet object-detection training, evaluation, configuration, and setup workflows.

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Use Chai Lab / Chai-1 for molecular structure prediction, input preparation, MSA/template setup, restraints, glycans, and repo-specific troubleshooting.

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Use Spotify Chartify to build tidy pandas/Bokeh charts, route plot workflows, customize styling, and diagnose output/configuration issues.

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Guides ChatGLM2-6B Transformers inference, local demos, FastAPI/OpenAI-compatible serving, C-Eval evaluation, and P-Tuning v2 fine-tuning.

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Operate ChatterBot conversational dialog engine workflows, including chatbot setup, training, logic adapters, storage backends, Django integration, and optional LLM adapters.

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Use Chonkie for text/document chunking, pipelines, embeddings, CLI/API serving, and storage integrations.

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Use Cirq to build, simulate, transform, serialize, validate, and provider-package quantum circuits.

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Use the city2graph 1.0.0 Python package to construct, validate, transform, and troubleshoot geospatial, spatial-topology, morphology, mobility, transportation, heterogeneous, and GNN-ready graphs.

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Use CLAM for weakly supervised computational pathology workflows on whole-slide images, from WSI patching through features, training, evaluation, and heatmaps.

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Use ClawBio for local-first bioinformatics agent workflows: install and run its skill library, route genomic or omics inputs, create reproducible reports, connect optional MCP or Nextflow integrations, and author or validate skills.

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Routes cleanlab data-centric AI workflows for finding label errors, dataset issues, outliers, annotator quality, and task-specific label-quality problems.

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Use CleanRL's single-file reinforcement learning scripts, evaluation utilities, experiment operations, and repository maintenance workflows safely.

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Use Brian2 for clock-driven spiking-neural-network modeling, simulation, synaptic connectivity, input generation, recording, physical-unit equations, spatial neurons, runtime code generation, and C++ standalone workflows.

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Route ClearML Python SDK tasks across experiment tracking, data/versioned storage, remote execution CLIs, automation pipelines, HPO, schedulers, routers, and services.

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Guides CLIP-as-service client, server, and CLIP search workflows for text/image embeddings, cross-modal ranking, and retrieval services.

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Use OpenAI CLIP for zero-shot image-text inference, prompt engineering, feature extraction, and responsible evaluation.

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Routes tasks for discovering NLP datasets in the CLUEDatasetSearch catalogue, including Chinese NLP classification, QA, matching, NER, generation, translation, corpus, and reading-comprehension resources.

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Routes CogDL graph-learning workflows for experiments, graph data, models, training wrappers, and pipeline apps.

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Use ColabFold for protein structure prediction workflows: validate FASTA/CSV/A3M inputs, generate MSAs, plan batch predictions, inspect outputs, and troubleshoot optional AlphaFold, MMseqs2, JAX, GPU, and OpenMM dependencies.

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Use richzhang/colorization PyTorch colorizers for automatic image colorization, Python API calls, preprocessing/postprocessing, and runtime troubleshooting.

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Use ColossalAI for distributed PyTorch training, large-model parallelism, Booster plugins, ShardFormer, Colossal-Inference, and first-party application workflow routing.

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Use ComfyUI as a modular AI content-creation engine: launch and automate the server, submit API workflows, validate graph JSON, author custom nodes, and configure model paths/backends.

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Use MosaicML Composer for PyTorch training loops, speedup methods, loggers, checkpoints, distributed launch, profiling, and model export.

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Operate Core ML Tools workflows for model conversion, Core ML artifact I/O, optimization, MIL debugging, and platform-aware troubleshooting.

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