Instructions to use birgermoell/Flashback-Bellman with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use birgermoell/Flashback-Bellman with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="birgermoell/Flashback-Bellman")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("birgermoell/Flashback-Bellman")
model = AutoModelForMultimodalLM.from_pretrained("birgermoell/Flashback-Bellman")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use birgermoell/Flashback-Bellman with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "birgermoell/Flashback-Bellman"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "birgermoell/Flashback-Bellman",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/birgermoell/Flashback-Bellman

SGLang

How to use birgermoell/Flashback-Bellman 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 "birgermoell/Flashback-Bellman" \
    --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": "birgermoell/Flashback-Bellman",
		"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 "birgermoell/Flashback-Bellman" \
        --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": "birgermoell/Flashback-Bellman",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use birgermoell/Flashback-Bellman with Docker Model Runner:
```
docker model run hf.co/birgermoell/Flashback-Bellman
```

Flashback-Bellman / mergekit_config.yml

birgermoell

Upload folder using huggingface_hub

c588d2b verified over 2 years ago

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	slices:
	- sources:
	- model: timpal0l/Mistral-7B-v0.1-flashback-v2
	layer_range: [0, 32]
	- model: RJuro/munin-neuralbeagle-7b
	layer_range: [0, 32]
	merge_method: slerp
	base_model: timpal0l/Mistral-7B-v0.1-flashback-v2
	parameters:
	t:
	- filter: self_attn
	value: [0, 0.5, 0.3, 0.7, 1]
	- filter: mlp
	value: [1, 0.5, 0.7, 0.3, 0]
	- value: 0.5
	dtype: bfloat16