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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert") model = AutoModelForMultimodalLM.from_pretrained("vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="vignesha7/DeepSeek-R1-Distill-Qwen-7B-Financial-Expert", max_seq_length=2048, )
- Xet hash:
- 78af695675c4fc8453e45a039d33450bec835340edcdac08f9a1af71f046ab0d
- Size of remote file:
- 11.4 MB
- SHA256:
- e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.