Instructions to use asynclee/SmolLM2-360M-Instruct-fc-cn-lora-F16-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asynclee/SmolLM2-360M-Instruct-fc-cn-lora-F16-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("asynclee/SmolLM2-360M-Instruct-fc-cn-lora-F16-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
metadata
base_model: lucaelin/SmolLM2-360M-Instruct-fc-cn-lora
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- llama-cpp
- gguf-my-lora
license: apache-2.0
language:
- en
asynclee/SmolLM2-360M-Instruct-fc-cn-lora-F16-GGUF
This LoRA adapter was converted to GGUF format from lucaelin/SmolLM2-360M-Instruct-fc-cn-lora via the ggml.ai's GGUF-my-lora space.
Refer to the original adapter repository for more details.
Use with llama.cpp
# with cli
llama-cli -m base_model.gguf --lora SmolLM2-360M-Instruct-fc-cn-lora-f16.gguf (...other args)
# with server
llama-server -m base_model.gguf --lora SmolLM2-360M-Instruct-fc-cn-lora-f16.gguf (...other args)
To know more about LoRA usage with llama.cpp server, refer to the llama.cpp server documentation.