license: cc-by-sa-4.0
datasets:
- acrastt/EverythingLM-V3-ShareGPT
language:
- en
library_name: transformers
pipeline_tag: text-generation
I'm constantly enhancing these model descriptions to provide you with the most relevant and comprehensive information
Marx-3B-V3 - GGUF
- Model creator: acrastt
- Original model: Marx-3B-V3
StableLM is a familiy of Models by Stability AI.
Note:
Current (as of. 2023-11-15) implementations of Llama.cpp only support GPU offloading up to 34 Layers. The model will crash immediately if -ngl is larger than 34. The model works fine however without any gpu acceleration.
About GGUF format
gguf
is the current file format used by the ggml
library.
A growing list of Software is using it and can therefore use this model.
The core project making use of the ggml library is the llama.cpp project by Georgi Gerganov
Quantization variants
There is a bunch of quantized files available to cater to your specific needs. Here's how to choose the best option for you:
Legacy quants
Q4_0, Q4_1, Q5_0, Q5_1 and Q8 are legacy
quantization types.
Nevertheless, they are fully supported, as there are several circumstances that cause certain model not to be compatible with the modern K-quants.
Note:
Now there's a new option to use K-quants even for previously 'incompatible' models, although this involves some fallback solution that makes them not real K-quants. More details can be found in affected model descriptions. (This mainly refers to Falcon 7b and Starcoder models)
K-quants
K-quants are designed with the idea that different levels of quantization in specific parts of the model can optimize performance, file size, and memory load. So, if possible, use K-quants. With a Q6_K, you'll likely find it challenging to discern a quality difference from the original model - ask your model two times the same question and you may encounter bigger quality differences.
Original Model Card:
This is StableLM 3B 4E1T(Licensed under CC BY-SA 4.0.) finetuned on EverythingLM Data V3(ShareGPT Format) for 2 epochs using QLoRA.
Prompt template:
### HUMAN:
{prompt}
### RESPONSE:
Note that this model have the EOS token of <|endoftext|>
instead of <\s>
.
GPTQ quantizations available here.
End of original Model File
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