Transformers
GGUF
text-generation-inference
unsloth
mistral
Mistral_Star
Mistral_Quiet
Mistral
Mixtral
Question-Answer
Token-Classification
Sequence-Classification
SpydazWeb-AI
chemistry
biology
legal
code
climate
medical
LCARS_AI_StarTrek_Computer
chain-of-thought
tree-of-knowledge
forest-of-thoughts
visual-spacial-sketchpad
alpha-mind
knowledge-graph
entity-detection
encyclopedia
wikipedia
stack-exchange
Reddit
Cyber-series
MegaMind
Cybertron
SpydazWeb
Spydaz
LCARS
star-trek
mega-transformers
Mulit-Mega-Merge
Multi-Lingual
Afro-Centric
African-Model
Ancient-One
Inference Endpoints
File size: 4,809 Bytes
94765d2 43a785c 94765d2 fcdd97e 94765d2 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 |
---
base_model: LeroyDyer/SpydazWeb_AI_HumanAI_008
datasets:
- neoneye/base64-decode-v2
- neoneye/base64-encode-v1
- VuongQuoc/Chemistry_text_to_image
- Kamizuru00/diagram_image_to_text
- LeroyDyer/Chemistry_text_to_image_BASE64
- LeroyDyer/AudioCaps-Spectrograms_to_Base64
- LeroyDyer/winogroud_text_to_imaget_BASE64
- LeroyDyer/chart_text_to_Base64
- LeroyDyer/diagram_image_to_text_BASE64
- mekaneeky/salt_m2e_15_3_instruction
- mekaneeky/SALT-languages-bible
- xz56/react-llama
- BeIR/hotpotqa
- arcee-ai/agent-data
language:
- en
- sw
- ig
- so
- es
- ca
- xh
- zu
- ha
- tw
- af
- hi
- bm
- su
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- Mistral_Star
- Mistral_Quiet
- Mistral
- Mixtral
- Question-Answer
- Token-Classification
- Sequence-Classification
- SpydazWeb-AI
- chemistry
- biology
- legal
- code
- climate
- medical
- LCARS_AI_StarTrek_Computer
- text-generation-inference
- chain-of-thought
- tree-of-knowledge
- forest-of-thoughts
- visual-spacial-sketchpad
- alpha-mind
- knowledge-graph
- entity-detection
- encyclopedia
- wikipedia
- stack-exchange
- Reddit
- Cyber-series
- MegaMind
- Cybertron
- SpydazWeb
- Spydaz
- LCARS
- star-trek
- mega-transformers
- Mulit-Mega-Merge
- Multi-Lingual
- Afro-Centric
- African-Model
- Ancient-One
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/LeroyDyer/SpydazWeb_AI_HumanAI_008
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-i1-GGUF
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.
## Provided Quants
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q2_K.gguf) | Q2_K | 2.8 | |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q3_K_S.gguf) | Q3_K_S | 3.3 | |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q3_K_M.gguf) | Q3_K_M | 3.6 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q3_K_L.gguf) | Q3_K_L | 3.9 | |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.IQ4_XS.gguf) | IQ4_XS | 4.0 | |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.2 | fast on arm, low quality |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q4_K_M.gguf) | Q4_K_M | 4.5 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q5_K_S.gguf) | Q5_K_S | 5.1 | |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q5_K_M.gguf) | Q5_K_M | 5.2 | |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q6_K.gguf) | Q6_K | 6.0 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.Q8_0.gguf) | Q8_0 | 7.8 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/SpydazWeb_AI_HumanAI_008-GGUF/resolve/main/SpydazWeb_AI_HumanAI_008.f16.gguf) | f16 | 14.6 | 16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
## FAQ / Model Request
See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.
## Thanks
I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.
<!-- end -->
|