Text Generation
GGUF
English
shining-valiant
shining-valiant-2
valiant
valiant-labs
llama
llama-3.1
llama-3.1-instruct
llama-3.1-instruct-8b
llama-3
llama-3-instruct
llama-3-instruct-8b
8b
science
physics
biology
chemistry
compsci
computer-science
engineering
technical
conversational
chat
instruct
TensorBlock
GGUF
Eval Results
Inference Endpoints
Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
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README.md
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1 |
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---
|
2 |
+
language:
|
3 |
+
- en
|
4 |
+
pipeline_tag: text-generation
|
5 |
+
tags:
|
6 |
+
- shining-valiant
|
7 |
+
- shining-valiant-2
|
8 |
+
- valiant
|
9 |
+
- valiant-labs
|
10 |
+
- llama
|
11 |
+
- llama-3.1
|
12 |
+
- llama-3.1-instruct
|
13 |
+
- llama-3.1-instruct-8b
|
14 |
+
- llama-3
|
15 |
+
- llama-3-instruct
|
16 |
+
- llama-3-instruct-8b
|
17 |
+
- 8b
|
18 |
+
- science
|
19 |
+
- physics
|
20 |
+
- biology
|
21 |
+
- chemistry
|
22 |
+
- compsci
|
23 |
+
- computer-science
|
24 |
+
- engineering
|
25 |
+
- technical
|
26 |
+
- conversational
|
27 |
+
- chat
|
28 |
+
- instruct
|
29 |
+
- TensorBlock
|
30 |
+
- GGUF
|
31 |
+
base_model: ValiantLabs/Llama3.1-8B-ShiningValiant2
|
32 |
+
datasets:
|
33 |
+
- sequelbox/Celestia
|
34 |
+
- sequelbox/Spurline
|
35 |
+
- sequelbox/Supernova
|
36 |
+
model_type: llama
|
37 |
+
license: llama3.1
|
38 |
+
model-index:
|
39 |
+
- name: Llama3.1-8B-ShiningValiant2
|
40 |
+
results:
|
41 |
+
- task:
|
42 |
+
type: text-generation
|
43 |
+
name: Text Generation
|
44 |
+
dataset:
|
45 |
+
name: Winogrande (5-Shot)
|
46 |
+
type: Winogrande
|
47 |
+
args:
|
48 |
+
num_few_shot: 5
|
49 |
+
metrics:
|
50 |
+
- type: acc
|
51 |
+
value: 75.85
|
52 |
+
name: acc
|
53 |
+
- task:
|
54 |
+
type: text-generation
|
55 |
+
name: Text Generation
|
56 |
+
dataset:
|
57 |
+
name: MMLU College Biology (5-Shot)
|
58 |
+
type: MMLU
|
59 |
+
args:
|
60 |
+
num_few_shot: 5
|
61 |
+
metrics:
|
62 |
+
- type: acc
|
63 |
+
value: 68.75
|
64 |
+
name: acc
|
65 |
+
- type: acc
|
66 |
+
value: 73.23
|
67 |
+
name: acc
|
68 |
+
- type: acc
|
69 |
+
value: 46.0
|
70 |
+
name: acc
|
71 |
+
- type: acc
|
72 |
+
value: 44.33
|
73 |
+
name: acc
|
74 |
+
- type: acc
|
75 |
+
value: 53.19
|
76 |
+
name: acc
|
77 |
+
- type: acc
|
78 |
+
value: 37.25
|
79 |
+
name: acc
|
80 |
+
- type: acc
|
81 |
+
value: 42.38
|
82 |
+
name: acc
|
83 |
+
- type: acc
|
84 |
+
value: 56.0
|
85 |
+
name: acc
|
86 |
+
- type: acc
|
87 |
+
value: 63.0
|
88 |
+
name: acc
|
89 |
+
- type: acc
|
90 |
+
value: 63.16
|
91 |
+
name: acc
|
92 |
+
- task:
|
93 |
+
type: text-generation
|
94 |
+
name: Text Generation
|
95 |
+
dataset:
|
96 |
+
name: IFEval (0-Shot)
|
97 |
+
type: HuggingFaceH4/ifeval
|
98 |
+
args:
|
99 |
+
num_few_shot: 0
|
100 |
+
metrics:
|
101 |
+
- type: inst_level_strict_acc and prompt_level_strict_acc
|
102 |
+
value: 65.24
|
103 |
+
name: strict accuracy
|
104 |
+
source:
|
105 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2
|
106 |
+
name: Open LLM Leaderboard
|
107 |
+
- task:
|
108 |
+
type: text-generation
|
109 |
+
name: Text Generation
|
110 |
+
dataset:
|
111 |
+
name: BBH (3-Shot)
|
112 |
+
type: BBH
|
113 |
+
args:
|
114 |
+
num_few_shot: 3
|
115 |
+
metrics:
|
116 |
+
- type: acc_norm
|
117 |
+
value: 26.35
|
118 |
+
name: normalized accuracy
|
119 |
+
source:
|
120 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2
|
121 |
+
name: Open LLM Leaderboard
|
122 |
+
- task:
|
123 |
+
type: text-generation
|
124 |
+
name: Text Generation
|
125 |
+
dataset:
|
126 |
+
name: MATH Lvl 5 (4-Shot)
|
127 |
+
type: hendrycks/competition_math
|
128 |
+
args:
|
129 |
+
num_few_shot: 4
|
130 |
+
metrics:
|
131 |
+
- type: exact_match
|
132 |
+
value: 11.63
|
133 |
+
name: exact match
|
134 |
+
source:
|
135 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2
|
136 |
+
name: Open LLM Leaderboard
|
137 |
+
- task:
|
138 |
+
type: text-generation
|
139 |
+
name: Text Generation
|
140 |
+
dataset:
|
141 |
+
name: GPQA (0-shot)
|
142 |
+
type: Idavidrein/gpqa
|
143 |
+
args:
|
144 |
+
num_few_shot: 0
|
145 |
+
metrics:
|
146 |
+
- type: acc_norm
|
147 |
+
value: 8.95
|
148 |
+
name: acc_norm
|
149 |
+
source:
|
150 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2
|
151 |
+
name: Open LLM Leaderboard
|
152 |
+
- task:
|
153 |
+
type: text-generation
|
154 |
+
name: Text Generation
|
155 |
+
dataset:
|
156 |
+
name: MuSR (0-shot)
|
157 |
+
type: TAUR-Lab/MuSR
|
158 |
+
args:
|
159 |
+
num_few_shot: 0
|
160 |
+
metrics:
|
161 |
+
- type: acc_norm
|
162 |
+
value: 7.19
|
163 |
+
name: acc_norm
|
164 |
+
source:
|
165 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2
|
166 |
+
name: Open LLM Leaderboard
|
167 |
+
- task:
|
168 |
+
type: text-generation
|
169 |
+
name: Text Generation
|
170 |
+
dataset:
|
171 |
+
name: MMLU-PRO (5-shot)
|
172 |
+
type: TIGER-Lab/MMLU-Pro
|
173 |
+
config: main
|
174 |
+
split: test
|
175 |
+
args:
|
176 |
+
num_few_shot: 5
|
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metrics:
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- type: acc
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value: 26.38
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2
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name: Open LLM Leaderboard
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+
---
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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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+
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## ValiantLabs/Llama3.1-8B-ShiningValiant2 - GGUF
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This repo contains GGUF format model files for [ValiantLabs/Llama3.1-8B-ShiningValiant2](https://huggingface.co/ValiantLabs/Llama3.1-8B-ShiningValiant2).
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+
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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 b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
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+
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+
## Prompt template
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+
|
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```
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+
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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+
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+
Cutting Knowledge Date: December 2023
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+
Today Date: 26 Jul 2024
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+
|
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{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
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+
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{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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+
```
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+
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## Model file specification
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [Llama3.1-8B-ShiningValiant2-Q2_K.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q2_K.gguf) | Q2_K | 2.961 GB | smallest, significant quality loss - not recommended for most purposes |
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| [Llama3.1-8B-ShiningValiant2-Q3_K_S.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q3_K_S.gguf) | Q3_K_S | 3.413 GB | very small, high quality loss |
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| [Llama3.1-8B-ShiningValiant2-Q3_K_M.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q3_K_M.gguf) | Q3_K_M | 3.743 GB | very small, high quality loss |
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+
| [Llama3.1-8B-ShiningValiant2-Q3_K_L.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q3_K_L.gguf) | Q3_K_L | 4.025 GB | small, substantial quality loss |
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+
| [Llama3.1-8B-ShiningValiant2-Q4_0.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q4_0.gguf) | Q4_0 | 4.341 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
225 |
+
| [Llama3.1-8B-ShiningValiant2-Q4_K_S.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q4_K_S.gguf) | Q4_K_S | 4.370 GB | small, greater quality loss |
|
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+
| [Llama3.1-8B-ShiningValiant2-Q4_K_M.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q4_K_M.gguf) | Q4_K_M | 4.583 GB | medium, balanced quality - recommended |
|
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+
| [Llama3.1-8B-ShiningValiant2-Q5_0.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q5_0.gguf) | Q5_0 | 5.215 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
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+
| [Llama3.1-8B-ShiningValiant2-Q5_K_S.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q5_K_S.gguf) | Q5_K_S | 5.215 GB | large, low quality loss - recommended |
|
229 |
+
| [Llama3.1-8B-ShiningValiant2-Q5_K_M.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q5_K_M.gguf) | Q5_K_M | 5.339 GB | large, very low quality loss - recommended |
|
230 |
+
| [Llama3.1-8B-ShiningValiant2-Q6_K.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q6_K.gguf) | Q6_K | 6.143 GB | very large, extremely low quality loss |
|
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+
| [Llama3.1-8B-ShiningValiant2-Q8_0.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/tree/main/Llama3.1-8B-ShiningValiant2-Q8_0.gguf) | Q8_0 | 7.954 GB | very large, extremely low quality loss - not recommended |
|
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+
|
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+
|
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+
## Downloading instruction
|
235 |
+
|
236 |
+
### Command line
|
237 |
+
|
238 |
+
Firstly, install Huggingface Client
|
239 |
+
|
240 |
+
```shell
|
241 |
+
pip install -U "huggingface_hub[cli]"
|
242 |
+
```
|
243 |
+
|
244 |
+
Then, downoad the individual model file the a local directory
|
245 |
+
|
246 |
+
```shell
|
247 |
+
huggingface-cli download tensorblock/Llama3.1-8B-ShiningValiant2-GGUF --include "Llama3.1-8B-ShiningValiant2-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
248 |
+
```
|
249 |
+
|
250 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
251 |
+
|
252 |
+
```shell
|
253 |
+
huggingface-cli download tensorblock/Llama3.1-8B-ShiningValiant2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
254 |
+
```
|