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:
- 30238b1b471097112e9cc124a9ef06acc3a0ce99a78d010c62a2e67c3e019e7a
- Size of remote file:
- 5.56 kB
- SHA256:
- 6066e59b7f43584003a53048ce8d7e7aae0b3f95a4021475091785e70e61f25c
路
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