๐ฌ Einstein-v6.1-Llama3-8B
This model is a full fine-tuned version of meta-llama/Meta-Llama-3-8B on diverse datasets.
This model is finetuned using 8xRTX3090 + 1xRTXA6000 using axolotl.
This model's training was sponsored by sablo.ai.
๐ฌ Prompt Template
You can use ChatML prompt template while using the model:
ChatML
<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{user}<|im_end|>
<|im_start|>assistant
{asistant}<|im_end|>
This prompt template is available as a chat template, which means you can format messages using the
tokenizer.apply_chat_template() method:
messages = [
{"role": "system", "content": "You are helpful AI asistant."},
{"role": "user", "content": "Hello!"}
]
gen_input = tokenizer.apply_chat_template(message, return_tensors="pt")
model.generate(**gen_input)
๐ Datasets used in this model
The datasets used to train this model are listed in the metadata section of the model card.
Please note that certain datasets mentioned in the metadata may have undergone filtering based on various criteria.
The results of this filtering process and its outcomes are in the data folder of this repository:
Weyaxi/Einstein-v6.1-Llama3-8B/data
๐ Quantizationed versions
GGUF @bartowski
ExLlamaV2 @bartowski
AWQ @solidrust
๐ฏ Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 68.60 |
| AI2 Reasoning Challenge (25-Shot) | 62.46 |
| HellaSwag (10-Shot) | 82.41 |
| MMLU (5-Shot) | 66.19 |
| TruthfulQA (0-shot) | 55.10 |
| Winogrande (5-shot) | 79.32 |
| GSM8k (5-shot) | 66.11 |
๐ฏ Open LLM Leaderboard v2 Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 19.99 |
| IFEval (0-Shot) | 45.68 |
| BBH (3-Shot) | 29.38 |
| MATH Lvl 5 (4-Shot) | 5.74 |
| GPQA (0-shot) | 4.25 |
| MuSR (0-shot) | 11.23 |
| MMLU-PRO (5-shot) | 23.68 |
๐ Some resources, discussions and reviews aboout this model
๐ฆ Announcement tweet:
๐ Reddit post in r/LocalLLaMA:
โถ๏ธ Youtube Video(s)
๐ฑ Octopus-V4-3B
- Octopus-V4-3B leverages the incredible physics capabilities of Einstein-v6.1-Llama3-8B in their model.
๐ค Additional information about training
This model is full fine-tuned for 2 epoch.
Total number of steps was 2026.
๐ค Acknowledgments
Thanks to sablo.ai for sponsoring this model.
Thanks to all the dataset authors mentioned in the datasets section.
Thanks to axolotl for making the repository I used to make this model.
Thanks to all open source AI community.
If you would like to support me:
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Model tree for Weyaxi/Einstein-v6.1-Llama3-8B
Base model
meta-llama/Meta-Llama-3-8BDatasets used to train Weyaxi/Einstein-v6.1-Llama3-8B
Collection including Weyaxi/Einstein-v6.1-Llama3-8B
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard62.460
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard82.410
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard66.190
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard55.100
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard79.320
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard66.110
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard45.680
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard29.380
