Feature Extraction
Transformers
Safetensors
qwen2
bnb-my-repo
text-embeddings-inference
4-bit precision
bitsandbytes
Instructions to use bnb-community/DeepSeek-R1-Distill-Qwen-32B-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bnb-community/DeepSeek-R1-Distill-Qwen-32B-bnb-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bnb-community/DeepSeek-R1-Distill-Qwen-32B-bnb-4bit")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("bnb-community/DeepSeek-R1-Distill-Qwen-32B-bnb-4bit") model = AutoModelForMultimodalLM.from_pretrained("bnb-community/DeepSeek-R1-Distill-Qwen-32B-bnb-4bit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78af695675c4fc8453e45a039d33450bec835340edcdac08f9a1af71f046ab0d
- Size of remote file:
- 11.4 MB
- SHA256:
- e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
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