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- Llama3.3-70B-CogniLink-Q3_K_L.gguf +3 -0
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- Llama3.3-70B-CogniLink-Q8_0/Llama3.3-70B-CogniLink-Q8_0-00001-of-00003.gguf +3 -0
- Llama3.3-70B-CogniLink-Q8_0/Llama3.3-70B-CogniLink-Q8_0-00002-of-00003.gguf +3 -0
- Llama3.3-70B-CogniLink-Q8_0/Llama3.3-70B-CogniLink-Q8_0-00003-of-00003.gguf +3 -0
- README.md +193 -0
.gitattributes
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README.md
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---
|
2 |
+
base_model: Daemontatox/Llama3.3-70B-CogniLink
|
3 |
+
tags:
|
4 |
+
- state-of-the-art
|
5 |
+
- reasoning
|
6 |
+
- chain-of-thought
|
7 |
+
- text-generation
|
8 |
+
- transformers
|
9 |
+
- llama
|
10 |
+
- instruction-tuning
|
11 |
+
- TensorBlock
|
12 |
+
- GGUF
|
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license: apache-2.0
|
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+
language:
|
15 |
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- en
|
16 |
+
datasets:
|
17 |
+
- Daemontatox/Deepthinking-COT
|
18 |
+
- gghfez/QwQ-LongCoT-130K-cleaned
|
19 |
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pipeline_tag: text-generation
|
20 |
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library_name: transformers
|
21 |
+
model-index:
|
22 |
+
- name: Llama3.3-70B-CogniLink
|
23 |
+
results:
|
24 |
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- task:
|
25 |
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type: text-generation
|
26 |
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name: Text Generation
|
27 |
+
dataset:
|
28 |
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name: IFEval (0-Shot)
|
29 |
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type: wis-k/instruction-following-eval
|
30 |
+
split: train
|
31 |
+
args:
|
32 |
+
num_few_shot: 0
|
33 |
+
metrics:
|
34 |
+
- type: inst_level_strict_acc and prompt_level_strict_acc
|
35 |
+
value: 69.31
|
36 |
+
name: averaged accuracy
|
37 |
+
source:
|
38 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
|
39 |
+
name: Open LLM Leaderboard
|
40 |
+
- task:
|
41 |
+
type: text-generation
|
42 |
+
name: Text Generation
|
43 |
+
dataset:
|
44 |
+
name: BBH (3-Shot)
|
45 |
+
type: SaylorTwift/bbh
|
46 |
+
split: test
|
47 |
+
args:
|
48 |
+
num_few_shot: 3
|
49 |
+
metrics:
|
50 |
+
- type: acc_norm
|
51 |
+
value: 52.12
|
52 |
+
name: normalized accuracy
|
53 |
+
source:
|
54 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
|
55 |
+
name: Open LLM Leaderboard
|
56 |
+
- task:
|
57 |
+
type: text-generation
|
58 |
+
name: Text Generation
|
59 |
+
dataset:
|
60 |
+
name: MATH Lvl 5 (4-Shot)
|
61 |
+
type: lighteval/MATH-Hard
|
62 |
+
split: test
|
63 |
+
args:
|
64 |
+
num_few_shot: 4
|
65 |
+
metrics:
|
66 |
+
- type: exact_match
|
67 |
+
value: 39.58
|
68 |
+
name: exact match
|
69 |
+
source:
|
70 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
|
71 |
+
name: Open LLM Leaderboard
|
72 |
+
- task:
|
73 |
+
type: text-generation
|
74 |
+
name: Text Generation
|
75 |
+
dataset:
|
76 |
+
name: GPQA (0-shot)
|
77 |
+
type: Idavidrein/gpqa
|
78 |
+
split: train
|
79 |
+
args:
|
80 |
+
num_few_shot: 0
|
81 |
+
metrics:
|
82 |
+
- type: acc_norm
|
83 |
+
value: 26.06
|
84 |
+
name: acc_norm
|
85 |
+
source:
|
86 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
|
87 |
+
name: Open LLM Leaderboard
|
88 |
+
- task:
|
89 |
+
type: text-generation
|
90 |
+
name: Text Generation
|
91 |
+
dataset:
|
92 |
+
name: MuSR (0-shot)
|
93 |
+
type: TAUR-Lab/MuSR
|
94 |
+
args:
|
95 |
+
num_few_shot: 0
|
96 |
+
metrics:
|
97 |
+
- type: acc_norm
|
98 |
+
value: 21.4
|
99 |
+
name: acc_norm
|
100 |
+
source:
|
101 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
|
102 |
+
name: Open LLM Leaderboard
|
103 |
+
- task:
|
104 |
+
type: text-generation
|
105 |
+
name: Text Generation
|
106 |
+
dataset:
|
107 |
+
name: MMLU-PRO (5-shot)
|
108 |
+
type: TIGER-Lab/MMLU-Pro
|
109 |
+
config: main
|
110 |
+
split: test
|
111 |
+
args:
|
112 |
+
num_few_shot: 5
|
113 |
+
metrics:
|
114 |
+
- type: acc
|
115 |
+
value: 46.37
|
116 |
+
name: accuracy
|
117 |
+
source:
|
118 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
|
119 |
+
name: Open LLM Leaderboard
|
120 |
+
---
|
121 |
+
|
122 |
+
<div style="width: auto; margin-left: auto; margin-right: auto">
|
123 |
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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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## Daemontatox/Llama3.3-70B-CogniLink - GGUF
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This repo contains GGUF format model files for [Daemontatox/Llama3.3-70B-CogniLink](https://huggingface.co/Daemontatox/Llama3.3-70B-CogniLink).
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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 b4823](https://github.com/ggml-org/llama.cpp/commit/5bbe6a9fe9a8796a9389c85accec89dbc4d91e39).
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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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<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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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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## Model file specification
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [Llama3.3-70B-CogniLink-Q2_K.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q2_K.gguf) | Q2_K | 26.375 GB | smallest, significant quality loss - not recommended for most purposes |
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| [Llama3.3-70B-CogniLink-Q3_K_S.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q3_K_S.gguf) | Q3_K_S | 30.912 GB | very small, high quality loss |
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| [Llama3.3-70B-CogniLink-Q3_K_M.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q3_K_M.gguf) | Q3_K_M | 34.267 GB | very small, high quality loss |
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| [Llama3.3-70B-CogniLink-Q3_K_L.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q3_K_L.gguf) | Q3_K_L | 37.141 GB | small, substantial quality loss |
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| [Llama3.3-70B-CogniLink-Q4_0.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q4_0.gguf) | Q4_0 | 39.970 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| [Llama3.3-70B-CogniLink-Q4_K_S.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q4_K_S.gguf) | Q4_K_S | 40.347 GB | small, greater quality loss |
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| [Llama3.3-70B-CogniLink-Q4_K_M.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q4_K_M.gguf) | Q4_K_M | 42.520 GB | medium, balanced quality - recommended |
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| [Llama3.3-70B-CogniLink-Q5_0.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q5_0.gguf) | Q5_0 | 48.657 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| [Llama3.3-70B-CogniLink-Q5_K_S.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q5_K_S.gguf) | Q5_K_S | 48.657 GB | large, low quality loss - recommended |
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| [Llama3.3-70B-CogniLink-Q5_K_M.gguf](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q5_K_M.gguf) | Q5_K_M | 49.950 GB | large, very low quality loss - recommended |
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+
| [Llama3.3-70B-CogniLink-Q6_K](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q6_K) | Q6_K | 57.888 GB | very large, extremely low quality loss |
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| [Llama3.3-70B-CogniLink-Q8_0](https://huggingface.co/tensorblock/Llama3.3-70B-CogniLink-GGUF/blob/main/Llama3.3-70B-CogniLink-Q8_0) | Q8_0 | 74.975 GB | very large, extremely low quality loss - not recommended |
|
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+
|
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+
|
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## Downloading instruction
|
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+
|
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+
### Command line
|
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+
|
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+
Firstly, install Huggingface Client
|
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+
|
179 |
+
```shell
|
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+
pip install -U "huggingface_hub[cli]"
|
181 |
+
```
|
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+
|
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+
Then, downoad the individual model file the a local directory
|
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+
|
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+
```shell
|
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+
huggingface-cli download tensorblock/Llama3.3-70B-CogniLink-GGUF --include "Llama3.3-70B-CogniLink-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
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+
```
|
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+
|
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+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
190 |
+
|
191 |
+
```shell
|
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+
huggingface-cli download tensorblock/Llama3.3-70B-CogniLink-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
193 |
+
```
|