Instructions to use Sao10K/Fimbulvetr-11B-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sao10K/Fimbulvetr-11B-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Sao10K/Fimbulvetr-11B-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Sao10K/Fimbulvetr-11B-v2") model = AutoModelForCausalLM.from_pretrained("Sao10K/Fimbulvetr-11B-v2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Sao10K/Fimbulvetr-11B-v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Sao10K/Fimbulvetr-11B-v2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Sao10K/Fimbulvetr-11B-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Sao10K/Fimbulvetr-11B-v2
- SGLang
How to use Sao10K/Fimbulvetr-11B-v2 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 "Sao10K/Fimbulvetr-11B-v2" \ --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": "Sao10K/Fimbulvetr-11B-v2", "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 "Sao10K/Fimbulvetr-11B-v2" \ --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": "Sao10K/Fimbulvetr-11B-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Sao10K/Fimbulvetr-11B-v2 with Docker Model Runner:
docker model run hf.co/Sao10K/Fimbulvetr-11B-v2
Cute girl to catch your attention.
https://huggingface.co/Sao10K/Fimbulvetr-11B-v2-GGUF <------ GGUF
Fimbulvetr-v2 - A Solar-Based Model
4/4 Status Update:
got a few reqs on wanting to support me: https://ko-fi.com/sao10k
anyway, status on v3 - Halted for time being, working on dataset work mainly. it's a pain, to be honest. the data I have isn't up to my standard for now. it's good, just not good enough
Prompt Formats - Alpaca or Vicuna. Either one works fine. Recommended SillyTavern Presets - Universal Light
Alpaca:
### Instruction:
<Prompt>
### Input:
<Insert Context Here>
### Response:
Vicuna:
System: <Prompt>
User: <Input>
Assistant:
Changelogs:
25/2 - repo renamed to remove test, model card redone. Model's officially out.
15/2 - Heavy testing complete. Good feedback.
Rant - Kept For Historical Reasons
Ramble to meet minimum length requirements:
Tbh i wonder if this shit is even worth doing. Like im just some broke guy lmao I've spent so much. And for what? I guess creds. Feels good when a model gets good feedback, but it seems like im invisible sometimes. I should be probably advertising myself and my models on other places but I rarely have the time to. Probably just internal jealousy sparking up here and now. Wahtever I guess.
Anyway cool EMT vocation I'm doing is cool except it pays peanuts, damn bruh 1.1k per month lmao. Government to broke to pay for shit. Pays the bills I suppose.
Anyway cool beans, I'm either going to continue the Solar Train or go to Mixtral / Yi when I get paid.
You still here?
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