Feature Extraction
Transformers
Safetensors
qwen3
text-embeddings-inference
8-bit precision
compressed-tensors
Instructions to use Wfiles/MNLP_M2_quantized_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wfiles/MNLP_M2_quantized_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Wfiles/MNLP_M2_quantized_model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Wfiles/MNLP_M2_quantized_model") model = AutoModel.from_pretrained("Wfiles/MNLP_M2_quantized_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
15e4bb5 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:c0acdaba32b920d640afb36af4396c91974e074735636e4016d17a8ed9c03730
size 11422753
|