FuseChat: Knowledge Fusion of Chat Models
Paper • 2408.07990 • Published • 15
How to use KaraKaraWitch/BlenderCartel-llama33-70B-Pt1 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="KaraKaraWitch/BlenderCartel-llama33-70B-Pt1")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("KaraKaraWitch/BlenderCartel-llama33-70B-Pt1")
model = AutoModelForCausalLM.from_pretrained("KaraKaraWitch/BlenderCartel-llama33-70B-Pt1")
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 KaraKaraWitch/BlenderCartel-llama33-70B-Pt1 with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KaraKaraWitch/BlenderCartel-llama33-70B-Pt1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "KaraKaraWitch/BlenderCartel-llama33-70B-Pt1",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/KaraKaraWitch/BlenderCartel-llama33-70B-Pt1
How to use KaraKaraWitch/BlenderCartel-llama33-70B-Pt1 with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "KaraKaraWitch/BlenderCartel-llama33-70B-Pt1" \
--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": "KaraKaraWitch/BlenderCartel-llama33-70B-Pt1",
"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 "KaraKaraWitch/BlenderCartel-llama33-70B-Pt1" \
--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": "KaraKaraWitch/BlenderCartel-llama33-70B-Pt1",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'How to use KaraKaraWitch/BlenderCartel-llama33-70B-Pt1 with Docker Model Runner:
docker model run hf.co/KaraKaraWitch/BlenderCartel-llama33-70B-Pt1
This is a merge of pre-trained language models created using mergekitty.
This model was merged using the SCE merge method using deepcogito/cogito-v2-preview-llama-70B as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
# Mirai is Mirai.
- model: Blackroot/Mirai-3.0-70B
# Narration
- model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0
# Claude 3 Sonnet/Opus prose style and quality
- model: Doctor-Shotgun/L3.3-70B-Magnum-Diamond
# "For the *Action*"?
- model: marcelbinz/Llama-3.1-Centaur-70B
# Better writing style, "creativity" shift. (fiction books)
- model: tdrussell/Llama-3-70B-Instruct-Storywriter
# Roleplaying and Story Writing
- model: Ppoyaa/MythoNemo-L3.1-70B-v1.0
# Classics (NeverSleep)
- model: NeverSleep/Lumimaid-v0.2-70B
# Sao10K
- model: Sao10K/70B-L3.3-mhnnn-x1
# Medical
- model: Black-Ink-Guild/Pernicious_Prophecy_70B
# Dialogue reinforcement
- model: LatitudeGames/Wayfarer-Large-70B-Llama-3.3
# Extra details
- model: TheDrummer/Anubis-70B-v1.1
# "Meanness"
- model: TheDrummer/Fallen-Llama-3.3-70B-v1
# Antique history
- model: nbeerbower/Llama3.1-Gutenberg-Doppel-70B
# Normalization?
- model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
# ERP/RP enhancement + Anime tilt
- model: zerofata/L3.3-GeneticLemonade-Final-v2-70B
merge_method: sce
base_model: deepcogito/cogito-v2-preview-llama-70B
select_topk: 0.2
parameters:
normalize: true
dtype: bfloat16