File size: 6,178 Bytes
f1f91df
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
---
license: apache-2.0
datasets:
- nicholasKluge/instruct-aira-dataset-v2
language:
- pt
metrics:
- accuracy
library_name: transformers
pipeline_tag: text-generation
tags:
- alignment
- instruction tuned
- text generation
- conversation
- assistant
- TensorBlock
- GGUF
widget:
- text: <s><instruction>Cite algumas bandas de rock famosas da década de 1960.</instruction>
  example_title: Exemplo
- text: <s><instruction>Quantos planetas existem no sistema solar?</instruction>
  example_title: Exemplo
- text: <s><instruction>Qual é o futuro do ser humano?</instruction>
  example_title: Exemplo
- text: <s><instruction>Qual o sentido da vida?</instruction>
  example_title: Exemplo
- text: <s><instruction>Como imprimir hello world em python?</instruction>
  example_title: Exemplo
- text: <s><instruction>Invente uma história sobre um encanador com poderes mágicos.</instruction>
  example_title: Exemplo
inference:
  parameters:
    repetition_penalty: 1.2
    temperature: 0.2
    top_k: 30
    top_p: 0.3
    max_new_tokens: 200
    length_penalty: 0.3
    early_stopping: true
co2_eq_emissions:
  emissions: 2530
  source: CodeCarbon
  training_type: fine-tuning
  geographical_location: United States of America
  hardware_used: NVIDIA A100-SXM4-40GB
base_model: nicholasKluge/TeenyTinyLlama-460m-Chat
---

<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
    <div style="display: flex; flex-direction: column; align-items: flex-start;">
        <p style="margin-top: 0.5em; margin-bottom: 0em;">
            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>
        </p>
    </div>
</div>

## nicholasKluge/TeenyTinyLlama-460m-Chat - GGUF

This repo contains GGUF format model files for [nicholasKluge/TeenyTinyLlama-460m-Chat](https://huggingface.co/nicholasKluge/TeenyTinyLlama-460m-Chat).

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).

<div style="text-align: left; margin: 20px 0;">
    <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;">
        Run them on the TensorBlock client using your local machine ↗
    </a>
</div>

## Prompt template

```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [TeenyTinyLlama-460m-Chat-Q2_K.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q2_K.gguf) | Q2_K | 0.186 GB | smallest, significant quality loss - not recommended for most purposes |
| [TeenyTinyLlama-460m-Chat-Q3_K_S.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q3_K_S.gguf) | Q3_K_S | 0.215 GB | very small, high quality loss |
| [TeenyTinyLlama-460m-Chat-Q3_K_M.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q3_K_M.gguf) | Q3_K_M | 0.236 GB | very small, high quality loss |
| [TeenyTinyLlama-460m-Chat-Q3_K_L.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q3_K_L.gguf) | Q3_K_L | 0.254 GB | small, substantial quality loss |
| [TeenyTinyLlama-460m-Chat-Q4_0.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q4_0.gguf) | Q4_0 | 0.273 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [TeenyTinyLlama-460m-Chat-Q4_K_S.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q4_K_S.gguf) | Q4_K_S | 0.275 GB | small, greater quality loss |
| [TeenyTinyLlama-460m-Chat-Q4_K_M.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q4_K_M.gguf) | Q4_K_M | 0.289 GB | medium, balanced quality - recommended |
| [TeenyTinyLlama-460m-Chat-Q5_0.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q5_0.gguf) | Q5_0 | 0.327 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [TeenyTinyLlama-460m-Chat-Q5_K_S.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q5_K_S.gguf) | Q5_K_S | 0.327 GB | large, low quality loss - recommended |
| [TeenyTinyLlama-460m-Chat-Q5_K_M.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q5_K_M.gguf) | Q5_K_M | 0.336 GB | large, very low quality loss - recommended |
| [TeenyTinyLlama-460m-Chat-Q6_K.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q6_K.gguf) | Q6_K | 0.385 GB | very large, extremely low quality loss |
| [TeenyTinyLlama-460m-Chat-Q8_0.gguf](https://huggingface.co/tensorblock/TeenyTinyLlama-460m-Chat-GGUF/blob/main/TeenyTinyLlama-460m-Chat-Q8_0.gguf) | Q8_0 | 0.498 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/TeenyTinyLlama-460m-Chat-GGUF --include "TeenyTinyLlama-460m-Chat-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/TeenyTinyLlama-460m-Chat-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```