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Solar, a new bot created by Upstage, is now available on Poe. As a top-ranked model on the HuggingFace Open LLM leaderboard, and a fine tune of Llama 2, Solar is a great example of the progress enabled by open source. Try now at https://poe.com/Solar-0-70b

SOLAR-0-70b-16bit model card

The model name has been changed from LLaMa-2-70b-instruct-v2 to SOLAR-0-70b-16bit

Model Details

Dataset Details

Used Datasets

  • Orca-style dataset
  • Alpaca-style dataset
  • No other dataset was used except for the dataset mentioned above
  • No benchmark test set or the training set are used

Prompt Template

### System:

### User:

### Assistant:


  • The followings are tested on A100 80GB
  • Our model can handle up to 10k+ input tokens, thanks to the rope_scaling option
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer

tokenizer = AutoTokenizer.from_pretrained("upstage/Llama-2-70b-instruct-v2")
model = AutoModelForCausalLM.from_pretrained(
    rope_scaling={"type": "dynamic", "factor": 2} # allows handling of longer inputs

prompt = "### User:\nThomas is healthy, but he has to go to the hospital. What could be the reasons?\n\n### Assistant:\n"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
del inputs["token_type_ids"]
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)

output = model.generate(**inputs, streamer=streamer, use_cache=True, max_new_tokens=float('inf'))
output_text = tokenizer.decode(output[0], skip_special_tokens=True)

Hardware and Software

Evaluation Results


Main Results

Model H4(Avg) ARC HellaSwag MMLU TruthfulQA MT_Bench
Llama-2-70b-instruct-v2(Ours, Open LLM Leaderboard) 73 71.1 87.9 70.6 62.2 7.44063
Llama-2-70b-instruct (Ours, Open LLM Leaderboard) 72.3 70.9 87.5 69.8 61 7.24375
llama-65b-instruct (Ours, Open LLM Leaderboard) 69.4 67.6 86.5 64.9 58.8
Llama-2-70b-hf 67.3 67.3 87.3 69.8 44.9
llama-30b-instruct-2048 (Ours, Open LLM Leaderboard) 67.0 64.9 84.9 61.9 56.3
llama-30b-instruct (Ours, Open LLM Leaderboard) 65.2 62.5 86.2 59.4 52.8
llama-65b 64.2 63.5 86.1 63.9 43.4
falcon-40b-instruct 63.4 61.6 84.3 55.4 52.5

Scripts for H4 Score Reproduction

  • Prepare evaluation environments:
# clone the repository
git clone https://github.com/EleutherAI/lm-evaluation-harness.git
# check out the specific commit
git checkout b281b0921b636bc36ad05c0b0b0763bd6dd43463
# change to the repository directory
cd lm-evaluation-harness

Contact Us

About Upstage

  • Upstage is a company specialized in Large Language Models (LLMs) and AI. We will help you build private LLMs and related applications. If you have a dataset to build domain specific LLMs or make LLM applications, please contact us at β–Ί click here to contact
  • As of August 1st, our 70B model has reached the top spot in openLLM rankings, marking itself as the current leading performer globally.
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