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🤗 pets

Parameter-Efficient Tuning at Scale with 🤗 Accelerate

Supported methods:

  1. Prefix Tuning
  2. P-Tuning
  3. Prompt Tuning
  4. LoRA [in backlog]

Models support matrix

Sequence Classification

Prefix Tuning P-Tuning Prompt Tuning LoRA
BERT ✅ ✅ ✅
RoBERTa ✅ ✅ ✅
GPT-2 ✅ ✅ ✅
Bloom ✅ ✅ ✅
OPT ✅ ✅ ✅
GPT-Neo ✅ ✅ ✅
GPT-J ✅ ✅ ✅
Deberta
Deberta-v2

Causal Language Modeling

Prefix Tuning P-Tuning Prompt Tuning LoRA
GPT-2 ✅ ✅ ✅
Bloom ✅ ✅ ✅
OPT ✅ ✅ ✅
GPT-Neo ✅ ✅ ✅
GPT-J ✅ ✅ ✅

Conditional Generation

Prefix Tuning P-Tuning Prompt Tuning LoRA
T5 ✅ ✅ ✅
BART ✅ ✅ ✅
S
Description
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Readme Apache-2.0
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