heegyu/open-korean-instructions
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How to use ifuseok/ft-solar-10.7b-v2.1-dpo with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="ifuseok/ft-solar-10.7b-v2.1-dpo")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("ifuseok/ft-solar-10.7b-v2.1-dpo")
model = AutoModelForCausalLM.from_pretrained("ifuseok/ft-solar-10.7b-v2.1-dpo")
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 ifuseok/ft-solar-10.7b-v2.1-dpo with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ifuseok/ft-solar-10.7b-v2.1-dpo"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "ifuseok/ft-solar-10.7b-v2.1-dpo",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/ifuseok/ft-solar-10.7b-v2.1-dpo
How to use ifuseok/ft-solar-10.7b-v2.1-dpo with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "ifuseok/ft-solar-10.7b-v2.1-dpo" \
--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": "ifuseok/ft-solar-10.7b-v2.1-dpo",
"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 "ifuseok/ft-solar-10.7b-v2.1-dpo" \
--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": "ifuseok/ft-solar-10.7b-v2.1-dpo",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'How to use ifuseok/ft-solar-10.7b-v2.1-dpo with Docker Model Runner:
docker model run hf.co/ifuseok/ft-solar-10.7b-v2.1-dpo
Input Models input text only.
Output Models generate text only.
Base Model yanolja/KoSOLAR-10.7B-v0.1
Training Dataset
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
repo = "ifuseok/sft-solar-10.7b-v2.1-dpo"
OpenOrca = AutoModelForCausalLM.from_pretrained(
repo,
return_dict=True,
torch_dtype=torch.float16,
device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
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