|
--- |
|
datasets: |
|
- emozilla/yarn-train-tokenized-32k-mistral |
|
metrics: |
|
- perplexity |
|
library_name: transformers |
|
license: apache-2.0 |
|
language: |
|
- en |
|
--- |
|
|
|
# Model Card: Yarn-Solar-10b-64k |
|
|
|
[Preprint (arXiv)](https://arxiv.org/abs/2309.00071) |
|
[GitHub](https://github.com/jquesnelle/yarn) |
|
 |
|
|
|
## Model Description |
|
|
|
Yarn-Solar-10b-64k is a state-of-the-art language model for long context, further pretrained on two billion long context tokens using the YaRN extension method. |
|
It is an extension of [SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0) and supports a 64k token context window. |
|
|
|
To use, pass `trust_remote_code=True` when loading the model, for example |
|
|
|
```python |
|
model = AutoModelForCausalLM.from_pretrained("NousResearch/Yarn-Solar-10b-64k", |
|
attn_implementation="flash_attention_2", |
|
torch_dtype=torch.bfloat16, |
|
device_map="auto", |
|
trust_remote_code=True) |
|
``` |
|
|
|
In addition you will need to use the latest version of `transformers` |
|
```sh |
|
pip install git+https://github.com/huggingface/transformers |
|
``` |
|
|
|
## Benchmarks |
|
|
|
Long context benchmarks: |
|
| Model | Context Window | 4k PPL | 8k PPL | 16k PPL | 32k PPL | 64k PPL | |
|
|-------|---------------:|------:|----------:|-----:|-----:|------------:| |
|
| [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 8k | 3.09 | 2.96 | - | - | - | |
|
| [Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) | 64k | 3.18 | 3.04 | 2.65 | 2.44 | 2.20 | |
|
| [Yarn-Mistral-7b-128k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k) | 128k | 3.21 | 3.08 | 2.68 | 2.47 | 2.24 | |
|
| [SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0) | 4k | 3.07 | - | - | - | - | |
|
| [Yarn-Solar-10b-32k](https://huggingface.co/NousResearch/Yarn-Solar-10b-32k) | 32k | 3.09 | 2.95 | 2.57 | 2.31 | - | |
|
| **[Yarn-Solar-10b-64k](https://huggingface.co/NousResearch/Yarn-Solar-10b-64k)** | **64k** | **3.13** | **2.99** | **2.61** | **2.34** | **2.15** | |
|
|
|
Short context benchmarks showing that quality degradation is minimal: |
|
| Model | Context Window | ARC-c | Hellaswag | MMLU | Truthful QA | |
|
|-------|---------------:|------:|----------:|-----:|------------:| |
|
| [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 8k | 59.98 | 83.31 | 64.16 | 42.15 | |
|
| [Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) | 64k | 59.38 | 81.21 | 61.32 | 42.50 | |
|
| [Yarn-Mistral-7b-128k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k) | 128k | 58.87 | 80.58 | 60.64 | 42.46 | |
|
| [SOLAR-10.7B-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-v1.0) | 4k | 61.95 | 84.60 | 65.48 | 45.04 | |
|
| [Yarn-Solar-10b-32k](https://huggingface.co/NousResearch/Yarn-Solar-10b-32k) | 32k | 59.64 | 83.65 | 64.36 | 44.82 | |
|
| **[Yarn-Solar-10b-64k](https://huggingface.co/NousResearch/Yarn-Solar-10b-64k)** | **64k** | **59.21** | **83.08** | **63.57** | **45.70** | |
|
|
|
## Collaborators |
|
|
|
- [bloc97](https://github.com/bloc97): Methods, paper and evals |
|
- [@theemozilla](https://twitter.com/theemozilla): Methods, paper, model training, and evals |
|
- [@EnricoShippole](https://twitter.com/EnricoShippole): Model training |
|
- [honglu2875](https://github.com/honglu2875): Paper and evals |
|
|
|
The authors would like to thank LAION AI for their support of compute for this model. |
|
It was trained on the [JUWELS](https://www.fz-juelich.de/en/ias/jsc/systems/supercomputers/juwels) supercomputer. |
