Question Answering
Transformers
Safetensors
Korean
qwen2
text-generation
finance
accounting
stock
quant
economics
text-generation-inference
Instructions to use aiqwe/FinShibainu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aiqwe/FinShibainu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="aiqwe/FinShibainu")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("aiqwe/FinShibainu") model = AutoModelForCausalLM.from_pretrained("aiqwe/FinShibainu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b9f5b4df284e89e31435cc29b4670c32286beb97e7c64a35a393717d7c95210
- Size of remote file:
- 4.99 GB
- SHA256:
- 9e528ba38342c8eb6ae6e5f0e33f13c48b5fcc1cf179a74935bd0e8f2f0f4d56
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