SOLAR-0

About

What SOLAR-0 is

Updates 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 Developed by: Upstage Backbone Model: LLaMA-2 Language(s): English Library: HuggingFace Transformers License: Fine-tuned checkpoints is licensed under the Non-Commercial Creative Commons license (CC BY-NC-4.0) Where to send comments: Instructions on how to provide feedback or comments on a model can be found by opening an issue in the Hugging Face community's model repository Contact: For questions and comments about the model, please email contact@upstage.ai 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 Usage - The followings are tested on A100 80GB - Our model can handle up to 10k+ input tokens, thanks to the ropescaling option Hardware and Software Hardware: We utilized an A100x8 4 for training our model Training Factors: We fine-tuned this model using a combination of the DeepSpeed library and the HuggingFace Trainer / HuggingFace Accelerate Evaluation Results Overview - We conducted a performance evaluation following the tasks being evaluated on the Open LLM Leaderboard. We evaluated our model on four benchmark datasets, which include ARC-Challenge, HellaSwag, MMLU, and TruthfulQA We used the lm-evaluation-harness repository, specifically commit b281b0921b636bc36ad05c0b0b0763bd6dd43463. - We used MT-bench, a set of challenging multi-turn open-ended questions, to evaluate the models Main Results Scripts for H4 Score Reproduction - Prepare evaluation environments: 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 u

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How language models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys solar-0 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (solar-0 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"solar-0","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Licence

Commercial licence needed

Sources

Weights & code

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