Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,42 @@
|
|
1 |
-
---
|
2 |
-
license: apache-2.0
|
3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
language:
|
4 |
+
- en
|
5 |
+
base_model:
|
6 |
+
- sequelbox/Qwen3-4B-PlumEsper
|
7 |
+
pipeline_tag: text-generation
|
8 |
+
library_name: transformers
|
9 |
+
tags:
|
10 |
+
- text-generation-inference
|
11 |
+
---
|
12 |
+
|
13 |
+
# **Qwen3-4B-PlumEsper**
|
14 |
+
|
15 |
+
> PlumEsper is a merged language model created using MergeKit, combining the specialized strengths and general reasoning capabilities of Esper 3 4B and Shining Valiant 3 4B. Built on Qwen/Qwen3-4B as the base, the merge was performed using the DELLA merge method. This fusion brings together the expertise of two powerful models: ValiantLabs/Qwen3-4B-ShiningValiant3 and ValiantLabs/Qwen3-4B-Esper3, resulting in a balanced model with enhanced versatility across a wide range of reasoning tasks.
|
16 |
+
|
17 |
+
## Model Files
|
18 |
+
|
19 |
+
| File Name | Size | Precision |
|
20 |
+
|-----------|------|-----------|
|
21 |
+
| Qwen3-4B-PlumEsper.BF16.gguf | 8.05 GB | BF16 |
|
22 |
+
| Qwen3-4B-PlumEsper.F16.gguf | 8.05 GB | F16 |
|
23 |
+
| Qwen3-4B-PlumEsper.F32.gguf | 16.1 GB | F32 |
|
24 |
+
| Qwen3-4B-PlumEsper.Q2_K.gguf | 1.67 GB | Q2_K |
|
25 |
+
| Qwen3-4B-PlumEsper.Q3_K_L.gguf | 2.24 GB | Q3_K_L |
|
26 |
+
| Qwen3-4B-PlumEsper.Q3_K_M.gguf | 2.08 GB | Q3_K_M |
|
27 |
+
| Qwen3-4B-PlumEsper.Q3_K_S.gguf | 1.89 GB | Q3_K_S |
|
28 |
+
| Qwen3-4B-PlumEsper.Q4_K_M.gguf | 2.5 GB | Q4_K_M |
|
29 |
+
| Qwen3-4B-PlumEsper.Q4_K_S.gguf | 2.38 GB | Q4_K_S |
|
30 |
+
| Qwen3-4B-PlumEsper.Q5_K_M.gguf | 2.89 GB | Q5_K_M |
|
31 |
+
| Qwen3-4B-PlumEsper.Q5_K_S.gguf | 2.82 GB | Q5_K_S |
|
32 |
+
| Qwen3-4B-PlumEsper.Q6_K.gguf | 3.31 GB | Q6_K |
|
33 |
+
| Qwen3-4B-PlumEsper.Q8_0.gguf | 4.28 GB | Q8_0 |
|
34 |
+
|
35 |
+
## Quants Usage
|
36 |
+
|
37 |
+
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
|
38 |
+
|
39 |
+
Here is a handy graph by ikawrakow comparing some lower-quality quant
|
40 |
+
types (lower is better):
|
41 |
+
|
42 |
+

|