Results for “lora”
16 skills
orchestra-research Axolotl
Provides expert guidance for fine-tuning LLMs with Axolotl, covering YAML configs, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, and multimodal support.
10.4k · bundle
jeffallan Fine Tuning Expert
Fine-tune LLMs using LoRA, QLoRA, and PEFT with Hugging Face, including dataset preparation, hyperparameter tuning, evaluation, and deployment.
10.4k · bundle
orchestra-research Unsloth
Provides expert guidance for fast fine-tuning with Unsloth, including LoRA/QLoRA optimization, with 2-5x faster training and 50-80% less memory usage.
10.4k · bundle
majiayu000 Hqq Quantization
Quantize large language models to 8/4/3/2/1-bit precision without calibration data, using multiple optimized backends and integrations with HuggingFace Transformers, vLLM, and PEFT/LoRA.
567 · bundle
lord1egypt Peft Fine Tuning
Fine-tune large language models by training less than 1% of parameters using LoRA, QLoRA, and 25+ adapter methods, enabling efficient adaptation on limited GPU memory.
2
orchestra-research Peft Fine Tuning
Fine-tune large language models by training less than 1% of parameters using LoRA, QLoRA, and 25+ adapter methods, enabling efficient adaptation on consumer GPUs.
10.4k · bundle
More results
nvidia 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
orchestra-research Fine Tuning Openvla Oft
Fine-tunes and evaluates OpenVLA-OFT and OpenVLA-OFT+ policies for robot action generation with continuous action heads, LoRA adaptation, and FiLM conditioning on LIBERO simulation and ALOHA real-world setups.
10.4k · bundle
qhjqhj00 Hqq Quantization
Quantize LLMs to 8/4/3/2/1-bit precision without calibration data, using multiple backends and HuggingFace/vLLM integration.
3 · bundle
orchestra-research Implementing Llms Litgpt
Train, fine-tune, and deploy LLMs using LitGPT's clean implementations of 20+ architectures like Llama, Gemma, and Phi.
10.4k · bundle
lord1egypt Llava
Runs the open-source LLaVA vision-language model for image understanding, captioning, visual question answering, and multi-turn image conversations, including setup, inference, and training guidance.
2
orchestra-research Torchforge Rl Training
Train reinforcement learning models using torchforge, Meta's PyTorch-native RL library for scalable, algorithm-focused experimentation with GRPO, DAPO, and custom loss functions.
10.4k · bundle
muratcankoylan Book Sft Pipeline
Convert books into supervised fine-tuning datasets and train style-transfer models that replicate an author's voice.
16.9k · bundle
majiayu000 Sft
Fine-tune instruction-following LLMs with Unsloth's optimized SFTTrainer, covering dataset formatting, chat templates, training configuration, and thinking-model patterns.
567 · bundle
majiayu000 Dpo
Trains language models with Direct Preference Optimization using preference pairs, covering DPOTrainer setup, dataset preparation, and beta tuning for stable preference learning without explicit reward models.
567 · bundle
orchestra-research Hqq Quantization
Quantize large language models to 8/4/3/2/1-bit precision without calibration data, using multiple optimized backends for deployment with vLLM or HuggingFace Transformers.
10.4k · bundle