Results for “model-hub”
21 skillsHuggingface Hub
Operate Hugging Face Hub repositories, models, datasets, and Spaces via the hf CLI, including downloads, uploads, authentication, and compute jobs.
2
172 Rvc 7a57af2e
Guides downloading and configuring RVC voice conversion models, including HuBERT and index files, and running voice conversion scripts.
7 · bundle
Hf CLI
Manage Hugging Face Hub resources: download/upload models, datasets, spaces; manage repos, buckets, collections, discussions, and cache; run SQL queries on datasets; authenticate and manage tokens.
10.8k
Hf CLI
Manage Hugging Face Hub resources via the `hf` CLI: download and upload models, datasets, and spaces; manage buckets, cache, collections, discussions, and inference endpoints; run SQL queries on datasets.
2 · bundle
Huggingface Local Models
Search the Hugging Face Hub for llama.cpp-compatible GGUF models, select the right quantization, and run them locally with llama-cli or llama-server.
10.8k · bundle
Transformers
Load pre-trained models from Hugging Face Hub, run pipeline inference, generate text, and fine-tune models on NLP, vision, audio, and multimodal tasks using the Transformers library.
30.2k · bundle
More results
Tao Finetune Huggingface Model
Fine-tune HuggingFace CV, VLM, or LLM models on local NVIDIA GPUs using an NGC PyTorch container, with support for full or LoRA training, dataset handling, and optional model push to the Hub.
2.2k · bundle
Hf MCP
Search models, datasets, Spaces, and papers on Hugging Face Hub, retrieve repository details and documentation, run compute jobs, and use Gradio Spaces as AI tools via MCP server tools.
42.4k
Ml Modeling
Entrena modelos de machine learning con Scikit-learn, LightGBM y XGBoost, desde un baseline hasta un modelo productivo con validación robusta y explicabilidad.
0 · bundle
Llama Cpp
Run GGUF models locally with llama.cpp, including finding the right file on the Hugging Face Hub, installing, quantizing, serving, and using Python bindings.
2 · bundle
Huggingface Vision Trainer
Trains and fine-tunes vision models for object detection, image classification, and segmentation using Hugging Face Transformers on cloud GPUs, with automatic dataset validation and Hub persistence.
10.8k · bundle
Agent Platform Model Registry
Manage machine learning models in the Agent Platform Model Registry: list, describe, upload, update, and delete models and their versions.
14.4k
Agent Platform Tuning
Fine-tune open models or Gemini models using Agent Platform infrastructure, from environment setup through data preparation, job configuration, monitoring, and deployment.
14.4k · bundle
Hf MCP
Connects AI assistants to the Hugging Face Hub via MCP server tools to search models, datasets, Spaces, and papers, retrieve repository details and documentation, run compute jobs, and use Gradio Spaces as AI tools.
3 · bundle
Model Merging
Merge multiple fine-tuned models using mergekit to combine capabilities without retraining, covering SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.
10.4k · bundle
Mle Workflow
Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.
1
Mle Workflow
Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.
0
Hf MCP
Connects AI assistants to the Hugging Face Hub via MCP server tools to search models, datasets, Spaces, and papers, retrieve repo details and documentation, run compute jobs, and use Gradio Spaces as AI tools.
253
Huggingface Community Evals
Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware, with backend selection between vLLM, Transformers, and accelerate.
10.8k · bundle
Hf Mem
Estimates the memory required to load Safetensors or GGUF model weights for inference from the Hugging Face Hub, using HTTP Range requests without downloading weights.
10.8k
Hf Mem
Estimates GPU memory required to load Safetensors or GGUF model weights for inference from the Hugging Face Hub using HTTP Range requests, without downloading weights locally.
42.4k