Experimental Model Merge ⚗️
Collection
Experimental Model Merge using mergekit FP16 Weight • 7 items • Updated • 2
How to use bluuwhale/Neuropy-7B with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="bluuwhale/Neuropy-7B") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("bluuwhale/Neuropy-7B")
model = AutoModelForCausalLM.from_pretrained("bluuwhale/Neuropy-7B")How to use bluuwhale/Neuropy-7B with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bluuwhale/Neuropy-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "bluuwhale/Neuropy-7B",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/bluuwhale/Neuropy-7B
How to use bluuwhale/Neuropy-7B with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "bluuwhale/Neuropy-7B" \
--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": "bluuwhale/Neuropy-7B",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'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 "bluuwhale/Neuropy-7B" \
--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": "bluuwhale/Neuropy-7B",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use bluuwhale/Neuropy-7B with Docker Model Runner:
docker model run hf.co/bluuwhale/Neuropy-7B
This is a merge of pre-trained language models created using mergekit.
This model was merged using the SLERP merge method.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: ./merged/phase1
layer_range: [0, 32]
- model: Undi95/Toppy-M-7B
layer_range: [0, 32]
merge_method: slerp
base_model: ./merged/phase1
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 # fallback for rest of tensors
dtype: bfloat16
Base model
Undi95/Toppy-M-7B