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:
- 26615ae25ba2e66dc0da620306c329f140d89885209b31345b027038b5353bdb
- Size of remote file:
- 4.93 GB
- SHA256:
- be773804f780cf23d7efc6e0b3ec040f9bf4ba4c19076d73720346f9f4324db3
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