Instructions to use rabitt/Chinese-Alpaca-Plus-13B-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rabitt/Chinese-Alpaca-Plus-13B-GPTQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="rabitt/Chinese-Alpaca-Plus-13B-GPTQ")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("rabitt/Chinese-Alpaca-Plus-13B-GPTQ") model = AutoModelForCausalLM.from_pretrained("rabitt/Chinese-Alpaca-Plus-13B-GPTQ", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 936e57db8994e0e83d657cb86e359b072270b042760159c0bd0c4a8ead3c5d43
- Size of remote file:
- 7.62 GB
- SHA256:
- e365600a11aafaf7a37dd0a11479bce7f14b123c35706f89160bd4eadd29c3ea
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