Instructions to use saishf/Fett-Eris-Mix-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saishf/Fett-Eris-Mix-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="saishf/Fett-Eris-Mix-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("saishf/Fett-Eris-Mix-7B") model = AutoModelForCausalLM.from_pretrained("saishf/Fett-Eris-Mix-7B") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use saishf/Fett-Eris-Mix-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "saishf/Fett-Eris-Mix-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "saishf/Fett-Eris-Mix-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/saishf/Fett-Eris-Mix-7B
- SGLang
How to use saishf/Fett-Eris-Mix-7B 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 "saishf/Fett-Eris-Mix-7B" \ --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": "saishf/Fett-Eris-Mix-7B", "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 "saishf/Fett-Eris-Mix-7B" \ --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": "saishf/Fett-Eris-Mix-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use saishf/Fett-Eris-Mix-7B with Docker Model Runner:
docker model run hf.co/saishf/Fett-Eris-Mix-7B
General discussion/chatting.
Hey! Love me some context size.
Managing a stable/decent cohesion at, say, 12K?
Testing now :3
Also when using universal light this model likes to describe everything, its own actions to the t. but it keeps the messages short? not sure which model would cause that but i like it
Results.
It's sensitive as of now (easy to make go insane), it probably needs some form of fine-tuning. I'll see what i can do as i like the way it speaks
but it keeps the messages short
That's nice.
it works perfect with alpaca
As long as it works with at least a prompt format it should be fine.
