Downloads · 30 days
498
4% of all-time downloads
RichardErkhov/Evillain_-_StarDust_20B_v0.2-gguf
Evillain_-_StarDust_20B_v0.2-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
498
4% of all-time downloads
All-time downloads
11.4K
Public
Repo size
131 GB
Likes
1
Public
Click a slice to open those files.
.gguf140 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
StarDust_20B_v0.2 - GGUF
| Name | Quant method | Size |
|---|---|---|
| StarDust_20B_v0.2.Q2_K.gguf | Q2_K | 6.91GB |
| StarDust_20B_v0.2.IQ3_XS.gguf | IQ3_XS | 7.63GB |
| StarDust_20B_v0.2.IQ3_S.gguf | IQ3_S | 8.06GB |
| StarDust_20B_v0.2.Q3_K_S.gguf | Q3_K_S | 8.06GB |
| StarDust_20B_v0.2.IQ3_M.gguf | IQ3_M | 8.53GB |
| StarDust_20B_v0.2.Q3_K.gguf | Q3_K | 9.04GB |
| StarDust_20B_v0.2.Q3_K_M.gguf | Q3_K_M | 9.04GB |
| StarDust_20B_v0.2.Q3_K_L.gguf | Q3_K_L | 9.9GB |
| StarDust_20B_v0.2.IQ4_XS.gguf | IQ4_XS | 10.01GB |
| StarDust_20B_v0.2.Q4_0.gguf | Q4_0 | 10.52GB |
| StarDust_20B_v0.2.IQ4_NL.gguf | IQ4_NL | 10.57GB |
| StarDust_20B_v0.2.Q4_K_S.gguf | Q4_K_S | 7.56GB |
| StarDust_20B_v0.2.Q4_K.gguf | Q4_K | 5.57GB |
| StarDust_20B_v0.2.Q4_K_M.gguf | Q4_K_M | 4.12GB |
| StarDust_20B_v0.2.Q4_1.gguf | Q4_1 | 3.66GB |
| StarDust_20B_v0.2.Q5_0.gguf | Q5_0 | 2.97GB |
| StarDust_20B_v0.2.Q5_K_S.gguf | Q5_K_S | 2.04GB |
| StarDust_20B_v0.2.Q5_K.gguf | Q5_K | 1.65GB |
| StarDust_20B_v0.2.Q5_K_M.gguf | Q5_K_M | 1.39GB |
| StarDust_20B_v0.2.Q5_1.gguf | Q5_1 | 1.31GB |
| StarDust_20B_v0.2.Q6_K.gguf | Q6_K | 1.05GB |
| StarDust_20B_v0.2.Q8_0.gguf | Q8_0 | 0.99GB |
license: other library_name: transformers tags:
GGUF Version: StarDust_20B_v0.2-GGUF
Exllamav2 4.55bpw: Evillain/StarDust_20B_v0.2_exl2_4.55bpw
Experimental merge of 3 capable models. Main purpose was to keep the DarkForest adventuring quality while make it more consistent with prompt and context following, and also increase RP and dialogues variety.
This model is suitable for adventuring, should be fine also for storytelling, RP and ERP, but I don't have much of a time and imagination for testing.
I haven't tested this model much, actually, so it's all about an exploration of it's capabilities.
Should work well with Alpaca format(but I'm not sure, since I don't really know what I'm doing :D)
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Input:
{input}
### Response:
DaringMaid was tested with Undi/Ikaris SillyTavern presets for Noromaid: Context template, Instruct template, so maybe it have a sense to try my model with those templates too.
This is a merge of pre-trained language models created using mergekit.
My second ever merge, created in order to understand how everything works.
Firstly I merged athirdpath/Iambe-RP-v3-20b and Kooten/DaringMaid-20B, named it Dust and repeated the operation with TeeZee/DarkForest-20B-v2.0 as a base and Dust as second model.
This model was merged using the SLERP merge method.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: TeeZee/DarkForest-20B-v2.0
layer_range: [0, 62]
- model: Dust
layer_range: [0, 62]
merge_method: slerp
base_model: TeeZee/DarkForest-20B-v2.0
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
name: StarDust_20B_v0.2
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 59.46 |
| AI2 Reasoning Challenge (25-Shot) | 61.01 |
| HellaSwag (10-Shot) | 83.76 |
| MMLU (5-Shot) | 59.29 |
| TruthfulQA (0-shot) | 51.43 |
| Winogrande (5-shot) | 77.27 |
| GSM8k (5-shot) | 24.03 |