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Browse files- .gitattributes +12 -0
- Aira-2-1B1-Q2_K.gguf +3 -0
- Aira-2-1B1-Q3_K_L.gguf +3 -0
- Aira-2-1B1-Q3_K_M.gguf +3 -0
- Aira-2-1B1-Q3_K_S.gguf +3 -0
- Aira-2-1B1-Q4_0.gguf +3 -0
- Aira-2-1B1-Q4_K_M.gguf +3 -0
- Aira-2-1B1-Q4_K_S.gguf +3 -0
- Aira-2-1B1-Q5_0.gguf +3 -0
- Aira-2-1B1-Q5_K_M.gguf +3 -0
- Aira-2-1B1-Q5_K_S.gguf +3 -0
- Aira-2-1B1-Q6_K.gguf +3 -0
- Aira-2-1B1-Q8_0.gguf +3 -0
- README.md +111 -0
.gitattributes
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README.md
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---
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license: apache-2.0
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datasets:
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- nicholasKluge/instruct-aira-dataset
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language:
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- en
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metrics:
|
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- accuracy
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library_name: transformers
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tags:
|
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- alignment
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- instruction tuned
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- text generation
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- conversation
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- assistant
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- TensorBlock
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- GGUF
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pipeline_tag: text-generation
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widget:
|
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+
- text: Can you explain what is Machine Learning?<|endofinstruction|>
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example_title: Machine Learning
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- text: Do you know anything about virtue ethics?<|endofinstruction|>
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example_title: Ethics
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- text: How can I make my girlfriend happy?<|endofinstruction|>
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example_title: Advise
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inference:
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parameters:
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repetition_penalty: 1.2
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temperature: 0.2
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top_k: 30
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top_p: 0.3
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max_new_tokens: 200
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length_penalty: 0.3
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early_stopping: true
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co2_eq_emissions:
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emissions: 1710
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source: CodeCarbon
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training_type: fine-tuning
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geographical_location: Singapore
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hardware_used: NVIDIA A100-SXM4-40GB
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base_model: nicholasKluge/Aira-2-1B1
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---
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
|
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<div style="display: flex; justify-content: space-between; width: 100%;">
|
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<div style="display: flex; flex-direction: column; align-items: flex-start;">
|
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+
<p style="margin-top: 0.5em; margin-bottom: 0em;">
|
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+
Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
|
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</p>
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</div>
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</div>
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## nicholasKluge/Aira-2-1B1 - GGUF
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This repo contains GGUF format model files for [nicholasKluge/Aira-2-1B1](https://huggingface.co/nicholasKluge/Aira-2-1B1).
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
|
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+
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<div style="text-align: left; margin: 20px 0;">
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<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
|
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Run them on the TensorBlock client using your local machine ↗
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</a>
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</div>
|
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## Prompt template
|
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|
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```
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```
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## Model file specification
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|
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [Aira-2-1B1-Q2_K.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q2_K.gguf) | Q2_K | 0.432 GB | smallest, significant quality loss - not recommended for most purposes |
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| [Aira-2-1B1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q3_K_S.gguf) | Q3_K_S | 0.499 GB | very small, high quality loss |
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+
| [Aira-2-1B1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q3_K_M.gguf) | Q3_K_M | 0.548 GB | very small, high quality loss |
|
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+
| [Aira-2-1B1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q3_K_L.gguf) | Q3_K_L | 0.592 GB | small, substantial quality loss |
|
81 |
+
| [Aira-2-1B1-Q4_0.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q4_0.gguf) | Q4_0 | 0.637 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
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+
| [Aira-2-1B1-Q4_K_S.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q4_K_S.gguf) | Q4_K_S | 0.640 GB | small, greater quality loss |
|
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+
| [Aira-2-1B1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q4_K_M.gguf) | Q4_K_M | 0.668 GB | medium, balanced quality - recommended |
|
84 |
+
| [Aira-2-1B1-Q5_0.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q5_0.gguf) | Q5_0 | 0.766 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
85 |
+
| [Aira-2-1B1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q5_K_S.gguf) | Q5_K_S | 0.766 GB | large, low quality loss - recommended |
|
86 |
+
| [Aira-2-1B1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q5_K_M.gguf) | Q5_K_M | 0.782 GB | large, very low quality loss - recommended |
|
87 |
+
| [Aira-2-1B1-Q6_K.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q6_K.gguf) | Q6_K | 0.903 GB | very large, extremely low quality loss |
|
88 |
+
| [Aira-2-1B1-Q8_0.gguf](https://huggingface.co/tensorblock/Aira-2-1B1-GGUF/blob/main/Aira-2-1B1-Q8_0.gguf) | Q8_0 | 1.170 GB | very large, extremely low quality loss - not recommended |
|
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+
|
90 |
+
|
91 |
+
## Downloading instruction
|
92 |
+
|
93 |
+
### Command line
|
94 |
+
|
95 |
+
Firstly, install Huggingface Client
|
96 |
+
|
97 |
+
```shell
|
98 |
+
pip install -U "huggingface_hub[cli]"
|
99 |
+
```
|
100 |
+
|
101 |
+
Then, downoad the individual model file the a local directory
|
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|
103 |
+
```shell
|
104 |
+
huggingface-cli download tensorblock/Aira-2-1B1-GGUF --include "Aira-2-1B1-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
105 |
+
```
|
106 |
+
|
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+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
108 |
+
|
109 |
+
```shell
|
110 |
+
huggingface-cli download tensorblock/Aira-2-1B1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
111 |
+
```
|