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:
- e5d2e9c142f4639718cc873cb866bab965ff5c786107605f98b486ddae68281c
- Size of remote file:
- 5 GB
- SHA256:
- ec7016a2e22f646b1611c2b984b15fdfe45dd3cbfe08d04a1a0a0eaa5eea90a4
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