base_model: kno10/ende-chat-0.0.7
datasets:
- FreedomIntelligence/sharegpt-deutsch
- mayflowergmbh/oasst_de
- mayflowergmbh/dolly_15k_de
- mayflowergmbh/openschnabeltier_de
- mayflowergmbh/ultrachat_de
- WizardLM/WizardLM_evol_instruct_V2_196k
- mayflowergmbh/evol_instruct_de
- mayflowergmbh/alpaca-gpt4_de
- mayflowergmbh/dolphin_de
- mayflowergmbh/airoboros_de
language:
- en
- de
library_name: transformers
license: apache-2.0
no_imatrix: nan1
quantized_by: mradermacher
About
static quants of https://huggingface.co./kno10/ende-chat-0.0.7
Usage
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs 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 | Q2_K | 3.2 | |
| GGUF | IQ3_XS | 3.5 | |
| GGUF | Q3_K_S | 3.7 | |
| GGUF | IQ3_S | 3.7 | beats Q3_K* |
| GGUF | IQ3_M | 3.8 | |
| GGUF | Q3_K_M | 4.0 | lower quality |
| GGUF | Q3_K_L | 4.3 | |
| GGUF | IQ4_XS | 4.5 | |
| GGUF | Q4_K_S | 4.7 | fast, recommended |
| GGUF | Q4_K_M | 4.9 | fast, recommended |
| GGUF | Q5_K_S | 5.6 | |
| GGUF | Q5_K_M | 5.7 | |
| GGUF | Q6_K | 6.6 | very good quality |
| GGUF | Q8_0 | 8.5 | fast, best quality |
| GGUF | f16 | 15.9 | 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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.