Question Answering
Transformers
PyTorch
TensorBoard
Safetensors
qwen2
text-generation
unsloth
trl
sft
text-generation-inference
Instructions to use vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert") model = AutoModelForCausalLM.from_pretrained("vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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DeepSeek-R1 model finetuned for financial question answering.
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### Model Description
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DeepSeek-R1-Distill-Qwen-7B model
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** Vignesh
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- **Model type:** DeepSeek-R1
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DeepSeek-R1 model finetuned for financial question answering.
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### Model Description
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DeepSeek-R1-Distill-Qwen-7B model finetuned on TheFinAI/Fino1_Reasoning_Path_FinQA dataset.
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- **Developed by:** Vignesh
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- **Model type:** DeepSeek-R1
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