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---
base_model: Daemontatox/Llama3.3-70B-CogniLink
tags:
- state-of-the-art
- reasoning
- chain-of-thought
- text-generation
- transformers
- llama
- instruction-tuning
- TensorBlock
- GGUF
license: apache-2.0
language:
- en
datasets:
- Daemontatox/Deepthinking-COT
- gghfez/QwQ-LongCoT-130K-cleaned
pipeline_tag: text-generation
library_name: transformers
model-index:
- name: Llama3.3-70B-CogniLink
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: wis-k/instruction-following-eval
split: train
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 69.31
name: averaged accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: SaylorTwift/bbh
split: test
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 52.12
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: lighteval/MATH-Hard
split: test
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 39.58
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
split: train
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 26.06
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 21.4
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 46.37
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Daemontatox%2FLlama3.3-70B-CogniLink
name: Open LLM Leaderboard
---
<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>
[](https://tensorblock.co)
[](https://twitter.com/tensorblock_aoi)
[](https://discord.gg/Ej5NmeHFf2)
[](https://github.com/TensorBlock)
[](https://t.me/TensorBlock)
## Daemontatox/Llama3.3-70B-CogniLink - GGUF
This repo contains GGUF format model files for [Daemontatox/Llama3.3-70B-CogniLink](https://huggingface.co/Daemontatox/Llama3.3-70B-CogniLink).
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).
## Our projects
<table border="1" cellspacing="0" cellpadding="10">
<tr>
<th style="font-size: 25px;">Awesome MCP Servers</th>
<th style="font-size: 25px;">TensorBlock Studio</th>
</tr>
<tr>
<th><img src="https://imgur.com/2Xov7B7.jpeg" alt="Project A" width="450"/></th>
<th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Project B" width="450"/></th>
</tr>
<tr>
<th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
<th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
</tr>
<tr>
<th>
<a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style="
display: inline-block;
padding: 8px 16px;
background-color: #FF7F50;
color: white;
text-decoration: none;
border-radius: 6px;
font-weight: bold;
font-family: sans-serif;
">👀 See what we built 👀</a>
</th>
<th>
<a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
display: inline-block;
padding: 8px 16px;
background-color: #FF7F50;
color: white;
text-decoration: none;
border-radius: 6px;
font-weight: bold;
font-family: sans-serif;
">👀 See what we built 👀</a>
</th>
</tr>
</table>
## Prompt template
```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
## 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/Llama3.3-70B-CogniLink-GGUF --include "Llama3.3-70B-CogniLink-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/Llama3.3-70B-CogniLink-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
|