Feature Extraction
Transformers
Safetensors
English
llama
text-generation-inference
unsloth
text-embeddings-inference
Instructions to use srt1902/smollm2-xsum-grpo-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srt1902/smollm2-xsum-grpo-lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="srt1902/smollm2-xsum-grpo-lora")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("srt1902/smollm2-xsum-grpo-lora") model = AutoModel.from_pretrained("srt1902/smollm2-xsum-grpo-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded finetuned model
- Developed by: srt1902
- License: apache-2.0
- Finetuned from model : unsloth/SmolLM2-135M-Instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
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Model tree for srt1902/smollm2-xsum-grpo-lora
Base model
unsloth/SmolLM2-135M-Instruct-bnb-4bit