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--- |
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base_model: appvoid/palmer-002 |
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datasets: |
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- appvoid/no-prompt-15k |
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inference: false |
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language: |
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- en |
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license: apache-2.0 |
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model_creator: appvoid |
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model_name: palmer-002 |
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pipeline_tag: text-generation |
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quantized_by: afrideva |
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tags: |
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- gguf |
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- ggml |
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- quantized |
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- q2_k |
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- q3_k_m |
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- q4_k_m |
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- q5_k_m |
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- q6_k |
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- q8_0 |
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--- |
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# appvoid/palmer-002-GGUF |
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Quantized GGUF model files for [palmer-002](https://huggingface.co/appvoid/palmer-002) from [appvoid](https://huggingface.co/appvoid) |
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| Name | Quant method | Size | |
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| ---- | ---- | ---- | |
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| [palmer-002.fp16.gguf](https://huggingface.co/afrideva/palmer-002-GGUF/resolve/main/palmer-002.fp16.gguf) | fp16 | 2.20 GB | |
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| [palmer-002.q2_k.gguf](https://huggingface.co/afrideva/palmer-002-GGUF/resolve/main/palmer-002.q2_k.gguf) | q2_k | 483.12 MB | |
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| [palmer-002.q3_k_m.gguf](https://huggingface.co/afrideva/palmer-002-GGUF/resolve/main/palmer-002.q3_k_m.gguf) | q3_k_m | 550.82 MB | |
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| [palmer-002.q4_k_m.gguf](https://huggingface.co/afrideva/palmer-002-GGUF/resolve/main/palmer-002.q4_k_m.gguf) | q4_k_m | 668.79 MB | |
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| [palmer-002.q5_k_m.gguf](https://huggingface.co/afrideva/palmer-002-GGUF/resolve/main/palmer-002.q5_k_m.gguf) | q5_k_m | 783.02 MB | |
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| [palmer-002.q6_k.gguf](https://huggingface.co/afrideva/palmer-002-GGUF/resolve/main/palmer-002.q6_k.gguf) | q6_k | 904.39 MB | |
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| [palmer-002.q8_0.gguf](https://huggingface.co/afrideva/palmer-002-GGUF/resolve/main/palmer-002.q8_0.gguf) | q8_0 | 1.17 GB | |
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## Original Model Card: |
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 |
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# palmer |
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### a better base model |
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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 1.1b llama 2 model so you can use it with your favorite tools/frameworks. |
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### evaluation |
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|Model| ARC_C| HellaSwag| PIQA| Winogrande| |
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|------|-----|-----------|------|-------------| |
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|tinyllama-2t| 0.2807| 0.5463| 0.7067| 0.5683| |
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|palmer-001| 0.2807| 0.5524| 0.7106| **0.5896**| |
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|tinyllama-2.5t|0.3191|0.5896| 0.7307| 0.5872| |
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|palmer-002|**0.3242**|**0.5956**|**0.7345**|0.5888| |
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### training |
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Training took ~3.5 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. |
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### prompt |
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``` |
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no prompt |
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``` |
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<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> |
