Instructions to use FlareRebellion/WeirdCompound-v1.7-24b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FlareRebellion/WeirdCompound-v1.7-24b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FlareRebellion/WeirdCompound-v1.7-24b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FlareRebellion/WeirdCompound-v1.7-24b") model = AutoModelForCausalLM.from_pretrained("FlareRebellion/WeirdCompound-v1.7-24b") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use FlareRebellion/WeirdCompound-v1.7-24b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FlareRebellion/WeirdCompound-v1.7-24b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FlareRebellion/WeirdCompound-v1.7-24b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/FlareRebellion/WeirdCompound-v1.7-24b
- SGLang
How to use FlareRebellion/WeirdCompound-v1.7-24b 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 "FlareRebellion/WeirdCompound-v1.7-24b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FlareRebellion/WeirdCompound-v1.7-24b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "FlareRebellion/WeirdCompound-v1.7-24b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FlareRebellion/WeirdCompound-v1.7-24b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use FlareRebellion/WeirdCompound-v1.7-24b with Docker Model Runner:
docker model run hf.co/FlareRebellion/WeirdCompound-v1.7-24b
v1.8 when?
Cheers mate! No doubt, tinkering with this merge wouldn't be possible without your awesome fine tunes.
Genuinely curious what would happen if you removed Cydonia from the mix.
Genuinely curious what would happen if you removed Cydonia from the mix.
I thought this was an interesting challenge, so I gave it a shot. Basically, I kept everything the same, except I replaced Cydonia with MS3.2-The-Omega-Directive-24B-Unslop-v2.0
https://huggingface.co/FlareRebellion/BereavedCompound-v1.0-24b-GGUF (Full weights will take some time to upload.)
At the very least, it seems basically coherent. I didn't check whether some of the other models have some Cydonia in their lineage, so there might still be some leakage.