Question Answering
Transformers
Safetensors
English
llama
text-generation
trl
sft
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use jkeyyy/smart-contract-auditing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jkeyyy/smart-contract-auditing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="jkeyyy/smart-contract-auditing")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jkeyyy/smart-contract-auditing") model = AutoModelForCausalLM.from_pretrained("jkeyyy/smart-contract-auditing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 250151a057d352d9840f675c000b31754a0e373b737d5c5a9d11af2c5bdca4f5
- Size of remote file:
- 17.2 MB
- SHA256:
- 429e75e70f2c28a3366149c3d5ab2449b0c4b8313089fd4c244fec49f2100807
路
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