Instructions to use zerofata/L3.3-GeneticLemonade-Unleashed-70B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zerofata/L3.3-GeneticLemonade-Unleashed-70B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zerofata/L3.3-GeneticLemonade-Unleashed-70B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zerofata/L3.3-GeneticLemonade-Unleashed-70B") model = AutoModelForCausalLM.from_pretrained("zerofata/L3.3-GeneticLemonade-Unleashed-70B") 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 zerofata/L3.3-GeneticLemonade-Unleashed-70B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zerofata/L3.3-GeneticLemonade-Unleashed-70B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zerofata/L3.3-GeneticLemonade-Unleashed-70B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/zerofata/L3.3-GeneticLemonade-Unleashed-70B
- SGLang
How to use zerofata/L3.3-GeneticLemonade-Unleashed-70B 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 "zerofata/L3.3-GeneticLemonade-Unleashed-70B" \ --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": "zerofata/L3.3-GeneticLemonade-Unleashed-70B", "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 "zerofata/L3.3-GeneticLemonade-Unleashed-70B" \ --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": "zerofata/L3.3-GeneticLemonade-Unleashed-70B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use zerofata/L3.3-GeneticLemonade-Unleashed-70B with Docker Model Runner:
docker model run hf.co/zerofata/L3.3-GeneticLemonade-Unleashed-70B
Surprise Find :)
This model was a surprise find (for me). I'm using it for story generation, and it is very well rounded, follows instructions, gives interesting content with high variability. Well done, and thanks for publishing this!
PS: this model works much better for me than Nevoria, which was already quite good. No clue how it performs RP though :) (also, I haven't even bothered to try your presets - it seems pretty stable with any settings).
Thank you, that's high praise to be compared favorably to Nevoria! Happy to see the model holding up under different use cases. The jack of all trades nature it showed across different scenarios is what struck me with this as well.
The presets/settings are very much just there as a reference to make the model accessible for those who are unsure rather than a requirement.
This model was a surprise find (for me). I'm using it for story generation, and it is very well rounded, follows instructions, gives interesting content with high variability. Well done, and thanks for publishing this!
PS: this model works much better for me than Nevoria, which was already quite good. No clue how it performs RP though :) (also, I haven't even bothered to try your presets - it seems pretty stable with any settings).
What quants do you run 70bs at mate?
usually some 3-bit one, IQ3_M or Q3_K_S or something nearabouts.
usually some 3-bit one, IQ3_M or Q3_K_S or something nearabouts.
Cheers man.