Text Classification
Transformers
Safetensors
English
qwen3
text-generation
mcqa
multiple-choice
qwen
supervised-fine-tuning
mnlp
epfl
stem
text-embeddings-inference
Instructions to use youssefbelghmi/MNLP_M3_mcqa_model_true with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use youssefbelghmi/MNLP_M3_mcqa_model_true with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="youssefbelghmi/MNLP_M3_mcqa_model_true")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("youssefbelghmi/MNLP_M3_mcqa_model_true") model = AutoModelForCausalLM.from_pretrained("youssefbelghmi/MNLP_M3_mcqa_model_true") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a0f86f46043a550f136f6f2aa0d014429d3b0eb79c7c0aec7e01951185fd5a6
- Size of remote file:
- 6.03 kB
- SHA256:
- db5189fc59617e10393b5b5f769370791e961f0af894c2fba80a9de16cf543b3
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