Solar Pro
Collection
The most intelligent LLM on a single GPU
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Terms and Conditions
You shall not redistribute the original pre-trained model.
You are granted permission to use this model for your own fine-tuning purposes.
You may open-source the resulting fine-tuned model with any license, including for commercial use.
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solar-pro-preview-pretrained
solar-pro-preview-pretrained is a pre-trained model made by Upstage.
Usage
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("upstage/solar-pro-preview-pretrained")
model = AutoModelForCausalLM.from_pretrained(
"upstage/solar-pro-preview-pretrained",
device_map="cuda:0",
torch_dtype='auto',
trust_remote_code=True,
)
Fine-tuning
If you want to use it for chat purpose, please fine-tune it first. Please refer to the following chat template when fine-tuning.
# Generating Text for Multi-Turn Interaction
# For multi-turn conversations, use this approach:
context = [
{"role": "system", "content": "You are Solar, an AI bot by Upstage, loved by many people."},
{"role": "user", "content": "Hi, there!"},
{"role": "assistant", "content": "Hello, how can I help you?"},
{"role": "user", "content": "Send me a message of support."},
]
prompt = tokenizer.apply_chat_template(context, tokenize=False, add_generation_prompt=True)
print("# Input")
print(prompt)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, use_cache=True, max_new_tokens=4096)
print("# Output")
print(tokenizer.decode(outputs[0, inputs["input_ids"].shape[-1]:]))
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