Instructions to use KaraKaraWarehouse/UnFimbulvetr-20B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KaraKaraWarehouse/UnFimbulvetr-20B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="KaraKaraWarehouse/UnFimbulvetr-20B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("KaraKaraWarehouse/UnFimbulvetr-20B") model = AutoModelForCausalLM.from_pretrained("KaraKaraWarehouse/UnFimbulvetr-20B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use KaraKaraWarehouse/UnFimbulvetr-20B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "KaraKaraWarehouse/UnFimbulvetr-20B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KaraKaraWarehouse/UnFimbulvetr-20B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/KaraKaraWarehouse/UnFimbulvetr-20B
- SGLang
How to use KaraKaraWarehouse/UnFimbulvetr-20B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "KaraKaraWarehouse/UnFimbulvetr-20B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KaraKaraWarehouse/UnFimbulvetr-20B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "KaraKaraWarehouse/UnFimbulvetr-20B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KaraKaraWarehouse/UnFimbulvetr-20B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use KaraKaraWarehouse/UnFimbulvetr-20B with Docker Model Runner:
docker model run hf.co/KaraKaraWarehouse/UnFimbulvetr-20B
| base_model: ["Sao10K/Fimbulvetr-11B-v2"] | |
| library_name: transformers | |
| tags: | |
| - mergekit | |
| - merge | |
| # UnFimbulvetr-20B | |
|  | |
| *Waifu to catch your attention* | |
| This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). | |
| NOTE: *Only tested this just for a bit. YMMV.* | |
| ## Next Day Tests... | |
| Downloaded the GGUF model that someone quantized... And... nope. No. | |
| **Do not use model.** | |
| ## Merge Details | |
| ### Merge Method | |
| This model was merged using the passthrough merge method. | |
| ### Models Merged | |
| The following models were included in the merge: | |
| * Sao10K/Fimbulvetr-11B-v2 | |
| ### Configuration | |
| The following YAML configuration was used to produce this model: | |
| ```yaml | |
| slices: | |
| - sources: | |
| - model: FimbMagic | |
| layer_range: [0, 13] | |
| - sources: | |
| - model: FimbMagic | |
| layer_range: [8, 13] | |
| - sources: | |
| - model: FimbMagic | |
| layer_range: [12, 36] | |
| - sources: | |
| - model: FimbMagic | |
| layer_range: [12, 36] | |
| - sources: | |
| - model: FimbMagic | |
| layer_range: [36, 48] | |
| - sources: | |
| - model: FimbMagic | |
| layer_range: [36, 48] | |
| merge_method: passthrough | |
| dtype: bfloat16 | |
| ``` | |
| ### Additional Notes | |
| Fimbulvetr 11B is still a very good model. This model is for extreme trailblazers who wants to test stuff! | |
| Eval results? Don't bother. | |
| Last one before I sleep: *I'm so sorry Sao10K...* |