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:
- b91a92facfbc76bbf1962e816d0a3494c7b60e9fe040c266e9ef4bdd076b2761
- Size of remote file:
- 4.98 GB
- SHA256:
- 31319f4249c6ba502ccbb52e18143779173bf9e5497c98710701410010b0365f
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