IceLemonMedovukhaRP-7b (Ice0.101-20.03-RP-GRPO-2)
mistral v0.2 base
The words mead and medovukha are closely related and go back to the Proto-Indo-European word mรฉdสฐu (honey). Produced in Eastern Europe since pagan times, it remained popular well into the 19th century (unlike in Western Europe, where by the Middle Ages mead had already been mostly replaced by wine and beer).
Normal model IceMedovukhaRP-7b pls use it if you don't want to play with reasoning
ST settings, rules-lorebook look here
Use rules as examples and edit them as needed; it's not necessary to have my every rule.
Get last version of rules and ST settings preset, or ask me a questions you can here. on my AI related discord server for feedback, questions and other stuff.
Model slightly trained to use
<reasoning>...</reasoning>
To use it - import given ST settings preset(+-rules-lorebook)AND PUT
<reasoning>
in to Miscellaneous -> Start Reply With. I moved prompt to rules-lorebook for proper<reasoning>
setup. Use and edit it.
The model has a context limit of 32k tokens. However, the quality of responses from any model begins to decline after 16k tokens, with a more rapid degradation beyond 21k tokens. I recommend using 21k tokens as the maximum for optimal performance.
Exl2 Quants
Thx mradermacher for GGUF
All Quants
Download
I recommend using the huggingface-hub
Python library:
pip3 install huggingface-hub
To download the main
branch to a folder called IceLemonMedovukhaRP-7b
:
mkdir IceLemonMedovukhaRP-7b huggingface-cli download icefog72/IceLemonMedovukhaRP-7b --local-dir IceLemonMedovukhaRP-7b --local-dir-use-symlinks False
More advanced huggingface-cli download usage
If you remove the --local-dir-use-symlinks False
parameter, the files will instead be stored in the central Hugging Face cache directory (default location on Linux is: ~/.cache/huggingface
), and symlinks will be added to the specified --local-dir
, pointing to their real location in the cache. This allows for interrupted downloads to be resumed, and allows you to quickly clone the repo to multiple places on disk without triggering a download again. The downside, and the reason why I don't list that as the default option, is that the files are then hidden away in a cache folder and it's harder to know where your disk space is being used, and to clear it up if/when you want to remove a download model.
The cache location can be changed with the HF_HOME
environment variable, and/or the --cache-dir
parameter to huggingface-cli
.
For more documentation on downloading with huggingface-cli
, please see: HF -> Hub Python Library -> Download files -> Download from the CLI.
To accelerate downloads on fast connections (1Gbit/s or higher), install hf_transfer
:
pip3 install hf_transfer
And set environment variable HF_HUB_ENABLE_HF_TRANSFER
to 1
:
mkdir FOLDERNAME
HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download MODEL --local-dir FOLDERNAME --local-dir-use-symlinks False
Windows Command Line users: You can set the environment variable by running set HF_HUB_ENABLE_HF_TRANSFER=1
before the download command.
Uploaded model
- Developed by: icefog72
- License: cc-by-nc-4.0
- Finetuned from model : icefog72/Ice0.101-20.03-RP-GRPO-1
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
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