Summarization
Transformers
Safetensors
GGUF
English
qwen3
text-generation
small-language-model
length-control
abstractive-summarization
saransh
text-generation-inference
Instructions to use M37labsorg/Saransh-1.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M37labsorg/Saransh-1.7B with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="M37labsorg/Saransh-1.7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("M37labsorg/Saransh-1.7B") model = AutoModelForCausalLM.from_pretrained("M37labsorg/Saransh-1.7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle