Instructions to use mpasila/Viking-SlimSonnet-v1-LoRA-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mpasila/Viking-SlimSonnet-v1-LoRA-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("LumiOpen/Viking-7B") model = PeftModel.from_pretrained(base_model, "mpasila/Viking-SlimSonnet-v1-LoRA-7B") - Transformers
How to use mpasila/Viking-SlimSonnet-v1-LoRA-7B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mpasila/Viking-SlimSonnet-v1-LoRA-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use mpasila/Viking-SlimSonnet-v1-LoRA-7B with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mpasila/Viking-SlimSonnet-v1-LoRA-7B to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mpasila/Viking-SlimSonnet-v1-LoRA-7B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mpasila/Viking-SlimSonnet-v1-LoRA-7B to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="mpasila/Viking-SlimSonnet-v1-LoRA-7B", max_seq_length=2048, )
metadata
base_model: LumiOpen/Viking-7B
language:
- en
- fi
- sv
- 'no'
- da
- is
- nn
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
datasets:
- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
- mpasila/Sonnet3.5-SlimOrcaDedupCleaned-4k-context
library_name: peft
This is the fully trained version (with fixed formatting!!).
Dataset used: Gryphe/Sonnet3.5-SlimOrcaDedupCleaned which was further filtered to remove prompts/examples that are longer than 4076 tokens (removed about 385 examples).
Prompt format is: ChatML
Merged model: mpasila/Viking-SlimSonnet-v1-7B
Trained with regular LoRA (not quantized/QLoRA) and LoRA rank was 128 and Alpha set to 32. Trained for 1 epoch using A40 for about 23 hours.
Uploaded model
- Developed by: mpasila
- License: apache-2.0
- Finetuned from model : LumiOpen/Viking-7B
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
