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---
license: apache-2.0
language:
- en
datasets:
- appvoid/no-prompt-15k
pipeline_tag: text-generation
---
# palmer
### a better base model
palmer is a series of ~1b parameters language models fine-tuned to be used as base models instead of using custom prompts for tasks. This means that it can be further fine-tuned on more data with custom prompts as usual or be used for downstream tasks as any base model you can get. The model has the best of both worlds: some "bias" to act as an assistant, but also the abillity to predict the next-word from its internet knowledge base. It's a 1.3b llama 2 model so you can use it with your favorite tools/frameworks.
### evaluation
|Model| ARC_C| HellaSwag| PIQA| Winogrande|
|------|-----|-----------|------|-------------|
|tinyllama-2t| 0.2807| 0.5463| 0.7067| 0.5683|
|palmer-001 | 0.2807| 0.5524| 0.7106| 0.5896|
|sheared-1.3b| 0.2910| 0.5935| 0.7339| 0.5809|
|no-prompt-1.3b| 0.3157| **0.6022**| 0.7334| 0.5864|
|falcon-rw-1b-instruct-openorca (sota) | **0.3362**| 0.5997| **0.7394**| **0.6148**|
This model was trained on less than 25% of the dataset yet achieves competitive performance to current sota on open llm leaderboard. Wait for what it's coming!
### training
Training took ~5 P100 gpu hours. It was trained on 15,000 gpt-4 shuffled samples. palmer was fine-tuned using lower learning rates ensuring it keeps as much general knowledge as possible.
### prompt
```
no prompt
```
### limitations
Hallucinations are frequent, just as any transformer model this size.
<a href="https://ko-fi.com/appvoid" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 48px !important;width: 180px !important; filter: invert(70%);" ></a> |