Model Stock: All we need is just a few fine-tuned models
Paper • 2403.19522 • Published • 15
How to use Black-Ink-Guild/Blight with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="Black-Ink-Guild/Blight")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Black-Ink-Guild/Blight")
model = AutoModelForCausalLM.from_pretrained("Black-Ink-Guild/Blight")
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]:]))How to use Black-Ink-Guild/Blight with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Black-Ink-Guild/Blight"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Black-Ink-Guild/Blight",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/Black-Ink-Guild/Blight
How to use Black-Ink-Guild/Blight with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "Black-Ink-Guild/Blight" \
--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": "Black-Ink-Guild/Blight",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'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 "Black-Ink-Guild/Blight" \
--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": "Black-Ink-Guild/Blight",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'How to use Black-Ink-Guild/Blight with Docker Model Runner:
docker model run hf.co/Black-Ink-Guild/Blight
This is a merge of pre-trained language models created using mergekit.
This model was merged using the Model Stock merge method using /home/sicarius/text-generation-webui/models/huihui-ai_Llama-3.3-70B-Instruct-abliterated/ as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
base_model: /home/sicarius/text-generation-webui/models/huihui-ai_Llama-3.3-70B-Instruct-abliterated/
merge_method: model_stock
#dtype: float32
dtype: bfloat16
models:
- model: /home/sicarius/text-generation-webui/models/SicariusSicariiStuff_Negative_LLAMA_70B/
- model: /home/sicarius/text-generation-webui/models/Sao10K_L3.3-70B-Euryale-v2.3/
- model: /home/sicarius/text-generation-webui/models/invisietch_L3.1-70Blivion-v0.1-rc1-70B/
# - model: /home/sicarius/text-generation-webui/models/VAGOsolutions_Llama-3.1-SauerkrautLM-70b-Instruct/
# - model: /home/sicarius/text-generation-webui/models/Steelskull_L3.3-Nevoria-R1-70b/
# - model: /home/sicarius/text-generation-webui/models/Steelskull_L3.3-MS-Nevoria-70b/