{"id":23194,"library":"adapters","title":"Adapters","description":"A unified library for parameter-efficient and modular transfer learning, supporting adapter methods like LoRA, Bottleneck Adapters, AdapterPlus, DoRA, and ReFT. Built on Hugging Face Transformers. Current version: 1.3.0. Release cadence: irregular, roughly every 2-3 months.","status":"active","version":"1.3.0","language":"python","source_language":"en","source_url":"https://github.com/adapter-hub/adapters","tags":["parameter-efficient-fine-tuning","transfer-learning","adapter-hub","huggingface"],"install":[{"cmd":"pip install adapters","lang":"bash","label":"Install via pip"}],"dependencies":[{"reason":"Core dependency; adapters is built on top of HF Transformers","package":"transformers","optional":false}],"imports":[{"wrong":"from adapters import AutoAdapterModel","symbol":"AutoAdapterModel","correct":"from adapters import AutoAdapterModel"}],"quickstart":{"code":"from transformers import AutoTokenizer\nfrom adapters import AutoAdapterModel, LoRAConfig\n\ntokenizer = AutoTokenizer.from_pretrained(\"bert-base-uncased\")\nmodel = AutoAdapterModel.from_pretrained(\"bert-base-uncased\")\n\n# Add a LoRA adapter with configuration\nconfig = LoRAConfig(r=8, alpha=16)\nmodel.add_adapter(\"my_lora_adapter\", config=config)\nmodel.train_adapter(\"my_lora_adapter\")\n\n# Example: encode a sentence\ninputs = tokenizer(\"Hello, adapters!\", return_tensors=\"pt\")\noutputs = model(**inputs)\nprint(outputs.last_hidden_state.shape)","lang":"python","description":"Load a BERT model, add a LoRA adapter, and run a forward pass."},"warnings":[{"fix":"Pin transformers to the version listed in the adapters release (e.g., for adapters 1.3.0 use transformers >=4.51.0, <4.58.0).","message":"Each version of adapters supports a specific range of transformers versions. Using an incompatible transformers version may cause import errors or silent misbehavior. Check the release notes for the supported transformers version.","severity":"breaking","affected_versions":"all"},{"fix":"Use `model = AutoAdapterModel.from_pretrained(..., load_in_4bit=True, torch_dtype=torch.bfloat16)` and ensure bitsandbytes is installed.","message":"When using QLoRA with bnb (bitsandbytes), the quantized model must be loaded with `load_in_4bit=True` and `torch_dtype=torch.bfloat16`. Omitting these may cause runtime errors or incorrect behavior.","severity":"gotcha","affected_versions":">=0.2.0"},{"fix":"After adding an adapter, call `model.adapter_to('cuda')` or `model.adapter_to('cuda', dtype=torch.float16)`.","message":"The `adapter_to()` method is used to move adapter weights to a device and optionally convert dtype. Forgetting to call it after adding an adapter can leave weights on CPU, causing issues when training on GPU.","severity":"gotcha","affected_versions":">=0.2.1"}],"env_vars":null,"search_vec":"'-3':38 '1.3.0':31 '2':37 'adapt':1,14,19,49 'adapter-hub':48 'adapterplus':20 'bottleneck':18 'built':24 'cadenc':33 'current':29 'dora':21 'effici':8,42 'everi':36 'face':27 'fine':43 'hub':50 'hug':26 'huggingfac':51 'irregular':34 'learn':12,47 'librari':4 'like':16 'lora':17 'method':15 'modular':10 'month':39 'paramet':7,41 'parameter-effici':6 'parameter-efficient-fine-tun':40 'reft':23 'releas':32 'rough':35 'support':13 'transfer':11,46 'transfer-learn':45 'transform':28 'tune':44 'unifi':3 'version':30","created_at":"2026-05-01T08:06:28.572886+00:00","updated_at":"2026-05-01T08:06:28.572886+00:00","problems":{"verify_error":"Traceback (most recent call last):\n  File \"<string>\", line 1, in <module>\n  File \"/tmp/tmpcogaxqbf/venv/lib/python3.12/site-packages/adapters/__init__.py\", line 23, in <module>\n    from adapters.configuration.adapter_config import MultiTaskConfig\n  File \"/tmp/tmpcogaxqbf/venv/lib/python3.12/site-pac"},"ecosystem":"pypi","meta_description":null,"install_score":null,"quickstart_score":null,"quickstart_tag":null,"pypi_latest":"1.3.0","cli_name":"","cli_version":null,"type":"library","homepage":null,"github":"https://github.com/adapter-hub/adapters","docs":null,"changelog":null,"pypi":"https://pypi.org/project/adapters/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"categories":["llm-agents","ai-ml"],"base_url":null,"auth_type":null,"provenance":{"verified_status":"import_fail","verified_at":"2026-07-03","last_verified":"2026-07-03","next_check":"2026-07-10","install_tag":null}}