Text Generation
Transformers
PyTorch
Safetensors
llama
alpaca
cot
vicuna
uncensored
Merge
mix
text-generation-inference
Instructions to use CalderaAI/30B-Lazarus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CalderaAI/30B-Lazarus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CalderaAI/30B-Lazarus")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CalderaAI/30B-Lazarus") model = AutoModelForCausalLM.from_pretrained("CalderaAI/30B-Lazarus") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use CalderaAI/30B-Lazarus with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CalderaAI/30B-Lazarus" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CalderaAI/30B-Lazarus", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CalderaAI/30B-Lazarus
- SGLang
How to use CalderaAI/30B-Lazarus 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 "CalderaAI/30B-Lazarus" \ --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": "CalderaAI/30B-Lazarus", "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 "CalderaAI/30B-Lazarus" \ --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": "CalderaAI/30B-Lazarus", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CalderaAI/30B-Lazarus with Docker Model Runner:
docker model run hf.co/CalderaAI/30B-Lazarus
Adding Evaluation Results
#10 opened over 2 years ago
by
leaderboard-pr-bot
Citation
1
#9 opened almost 3 years ago
by
dmgcsilva
Can you add more details on how models were combined / combinations of models were LoRA'd?
#8 opened almost 3 years ago
by
surya-narayanan
Don't compress emb for context.
#7 opened almost 3 years ago
by
jackboot
GGML or GPTQ
1
#5 opened almost 3 years ago
by
sirus
Typo
1
#4 opened almost 3 years ago
by
mechtronicman
Observations
👍 1
2
#3 opened almost 3 years ago
by
Yuuru
Will there be other versions (ie. 7B/13B/65B)
2
#2 opened almost 3 years ago
by
flashvenom
Any methodology description?
👍 3
4
#1 opened almost 3 years ago
by
teknium