Update README.md
Browse files
README.md
CHANGED
@@ -51,3 +51,63 @@ datasets:
|
|
51 |
- teknium/GPTeacher-General-Instruct
|
52 |
- m-a-p/CodeFeedback-Filtered-Instruction
|
53 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
51 |
- teknium/GPTeacher-General-Instruct
|
52 |
- m-a-p/CodeFeedback-Filtered-Instruction
|
53 |
---
|
54 |
+
|
55 |
+
---
|
56 |
+
license: apache-2.0
|
57 |
+
quantized_by: suparious
|
58 |
+
pipeline_tag: text-generation
|
59 |
+
---
|
60 |
+
## Exllama v2 Quantizations of Einstein-v5-v0.2-7B
|
61 |
+
|
62 |
+
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.16">turboderp's ExLlamaV2 v0.0.16</a> for quantization.
|
63 |
+
|
64 |
+
Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
|
65 |
+
|
66 |
+
Original model: l3utterfly/Einstein-v5-v0.2-7B
|
67 |
+
|
68 |
+
Model Size: 7b
|
69 |
+
|
70 |
+
| Branch | Bits | lm_head bits | Dataset | Size | Description |
|
71 |
+
| ----- | ---- | ------- | ------- | ------- | ------------ |
|
72 |
+
| [8_0](https://huggingface.co/suparious/Einstein-v5-v0.2-7B-exl2/tree/8_0) | 8.0 | 8.0 | Default | 9.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
|
73 |
+
| [6_5](https://huggingface.co/suparious/Einstein-v5-v0.2-7B-exl2/tree/6_5) | 6.5 | 8.0 | Default | 8.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
|
74 |
+
| [5_0](https://huggingface.co/suparious/Einstein-v5-v0.2-7B-exl2/tree/5_0) | 5.0 | 6.0 | Default | 7.4 GB | Slightly lower perplexity vs 6.5. |
|
75 |
+
| [4_0](https://huggingface.co/suparious/Einstein-v5-v0.2-7B-exl2/tree/4_0) | 4.0 | 6.0 | Default | 6.5 GB | Just under GPTQ equivalent bits per weight. |
|
76 |
+
|
77 |
+
All VRAM requirements estimated from 16k context. For 32k context add ~2 GB.
|
78 |
+
|
79 |
+
<a href="https://huggingface.co/suparious/Einstein-v5-v0.2-7B-exl2/tree/4_0">4.0 bits per weight</a>
|
80 |
+
|
81 |
+
<a href="https://huggingface.co/suparious/Einstein-v5-v0.2-7B-exl2/tree/5_0">5.0 bits per weight</a>
|
82 |
+
|
83 |
+
<a href="https://huggingface.co/suparious/Einstein-v5-v0.2-7B-exl2/tree/6_5">6.5 bits per weight</a>
|
84 |
+
|
85 |
+
<a href="https://huggingface.co/suparious/Einstein-v5-v0.2-7B-exl2/tree/8_0">8.0 bits per weight</a>
|
86 |
+
|
87 |
+
## Download instructions
|
88 |
+
|
89 |
+
With git:
|
90 |
+
|
91 |
+
```shell
|
92 |
+
git clone --single-branch --branch 4_0 https://huggingface.co/suparious/Einstein-v5-v0.2-7B-exl2
|
93 |
+
```
|
94 |
+
|
95 |
+
With huggingface hub (credit to TheBloke and bartowski for instructions):
|
96 |
+
|
97 |
+
```shell
|
98 |
+
pip3 install huggingface-hub
|
99 |
+
```
|
100 |
+
|
101 |
+
To download the `main` (only useful if you only care about measurement.json) branch to a folder called `Einstein-v5-v0.2-7B-exl2`:
|
102 |
+
|
103 |
+
```shell
|
104 |
+
mkdir Einstein-v5-v0.2-7B-exl2
|
105 |
+
huggingface-cli download suparious/Einstein-v5-v0.2-7B-exl2 --local-dir Einstein-v5-v0.2-7B-exl2 --local-dir-use-symlinks False
|
106 |
+
```
|
107 |
+
|
108 |
+
To download from a different branch, add the `--revision` parameter:
|
109 |
+
|
110 |
+
```shell
|
111 |
+
mkdir Einstein-v5-v0.2-7B-exl2-6_5
|
112 |
+
huggingface-cli download suparious/Einstein-v5-v0.2-7B-exl2 --revision 6_5 --local-dir Einstein-v5-v0.2-7B-exl2-6_5 --local-dir-use-symlinks False
|
113 |
+
```
|