Instructions to use athirdpath/Iambe-Storyteller-20b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use athirdpath/Iambe-Storyteller-20b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="athirdpath/Iambe-Storyteller-20b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("athirdpath/Iambe-Storyteller-20b") model = AutoModelForCausalLM.from_pretrained("athirdpath/Iambe-Storyteller-20b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use athirdpath/Iambe-Storyteller-20b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "athirdpath/Iambe-Storyteller-20b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "athirdpath/Iambe-Storyteller-20b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/athirdpath/Iambe-Storyteller-20b
- SGLang
How to use athirdpath/Iambe-Storyteller-20b 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 "athirdpath/Iambe-Storyteller-20b" \ --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": "athirdpath/Iambe-Storyteller-20b", "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 "athirdpath/Iambe-Storyteller-20b" \ --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": "athirdpath/Iambe-Storyteller-20b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use athirdpath/Iambe-Storyteller-20b with Docker Model Runner:
docker model run hf.co/athirdpath/Iambe-Storyteller-20b
Dumb assistant, 🔥 author.
4-bit Examples with Alpaca
!!NSFW!! - 🔥Erotica Writing Example🔥 - !!NSFW!!
Thanks to Charles Goddard for the recipe.
The idea here is to "move" Iambe from being based on vanilla L2 to being based on sequelbox/DynamicFactor instead.
Because task_arithmetic uses the raw deltas, this should be similar to if the SFT had been done over DynamicFactor.
Recipe
merge_method: task_arithmetic
base_model: athirdpath/BigLlama-20b-v1.1 # Base model you want to "move out" from
models:
model: athirdpath/Iambe-20b-DARE-v2 # SFTd model you want to transfer
model: athirdpath/DoubleFactor-20b # Base model you want to "move in" to
parameters:
- weight: 1.0
dtype: bfloat16
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docker model run hf.co/athirdpath/Iambe-Storyteller-20b