diff --git a/README.md b/README.md
index 713e17c6..362cac32 100644
--- a/README.md
+++ b/README.md
@@ -140,20 +140,20 @@
## News
- 🎯 2024/03/06: The Yi-9B is open-sourced and available to the public.
+ 🎯 2024-03-06: The Yi-9B
is open-sourced and available to the public.
- Yi-9B stands out as the top performer among a range of similar-sized open-source models (including Mistral-7B, SOLAR-10.7B, Gemma-7B, DeepSeek-Coder-7B-Base-v1.5 and more), particularly excelling in code, math, common-sense reasoning, and reading comprehension.
+Yi-9B
stands out as the top performer among a range of similar-sized open-source models (including Mistral-7B, SOLAR-10.7B, Gemma-7B, DeepSeek-Coder-7B-Base-v1.5 and more), particularly excelling in code, math, common-sense reasoning, and reading comprehension.
- 🎯 2024/01/23: The Yi-VL models, Yi-VL-34B
and Yi-VL-6B
, are open-sourced and available to the public.
+ 🎯 2024-01-23: The Yi-VL models, Yi-VL-34B
and Yi-VL-6B
, are open-sourced and available to the public.
Yi-VL-34B
has ranked first among all existing open-source models in the latest benchmarks, including MMMU and CMMMU (based on data available up to January 2024).
-🎯 2023/11/23: Chat models are open-sourced and available to the public.
+🎯 2023-11-23: Chat models are open-sourced and available to the public.
This release contains two chat models based on previously released base models, two 8-bit models quantized by GPTQ, and two 4-bit models quantized by AWQ.
- `Yi-34B-Chat`
@@ -170,11 +170,11 @@ You can try some of them interactively at:
- 🔔 2023/11/23: The Yi Series Models Community License Agreement is updated to v2.1.
+ 🔔 2023-11-23: The Yi Series Models Community License Agreement is updated to v2.1.
-🔥 2023/11/08: Invited test of Yi-34B chat model.
+🔥 2023-11-08: Invited test of Yi-34B chat model.
Application form:
- [English](https://cn.mikecrm.com/l91ODJf)
@@ -182,13 +182,13 @@ You can try some of them interactively at:
-🎯 2023/11/05: The base models, Yi-6B-200K
and Yi-34B-200K
, are open-sourced and available to the public.
+🎯 2023-11-05: The base models, Yi-6B-200K
and Yi-34B-200K
, are open-sourced and available to the public.
This release contains two base models with the same parameter sizes as the previous
release, except that the context window is extended to 200K.
-🎯 2023/11/02: The base models, Yi-6B
and Yi-34B
, are open-sourced and available to the public.
+🎯 2023-11-02: The base models, Yi-6B
and Yi-34B
, are open-sourced and available to the public.
The first public release contains two bilingual (English/Chinese) base models
with the parameter sizes of 6B and 34B. Both of them are trained with 4K
sequence length and can be extended to 32K during inference time.
@@ -927,11 +927,11 @@ Before deploying Yi in your environment, make sure your hardware meets the follo
| Model | Minimum VRAM | Recommended GPU Example |
|----------------------|--------------|:-------------------------------------:|
-| Yi-6B-Chat | 15 GB | RTX 3090
RTX 4090
A10
A30 |
-| Yi-6B-Chat-4bits | 4 GB | RTX 3060
RTX 4060 |
-| Yi-6B-Chat-8bits | 8 GB | RTX 3070
RTX 4060 |
+| Yi-6B-Chat | 15 GB | 1 x RTX 3090
1 x RTX 4090
A10
A30 |
+| Yi-6B-Chat-4bits | 4 GB | 1 x RTX 3060
1 x RTX 4060 |
+| Yi-6B-Chat-8bits | 8 GB | 1 x RTX 3070
1 x RTX 4060 |
| Yi-34B-Chat | 72 GB | 4 x RTX 4090
A800 (80GB) |
-| Yi-34B-Chat-4bits | 20 GB | RTX 3090
RTX 4090
A10
A30
A100 (40GB) |
+| Yi-34B-Chat-4bits | 20 GB | 1 x RTX 3090
1 x RTX 4090
A10
A30
A100 (40GB) |
| Yi-34B-Chat-8bits | 38 GB | 2 x RTX 3090
2 x RTX 4090
A800 (40GB) |
Below are detailed minimum VRAM requirements under different batch use cases.
@@ -949,7 +949,7 @@ Below are detailed minimum VRAM requirements under different batch use cases.
| Model | Minimum VRAM | Recommended GPU Example |
|----------------------|--------------|:-------------------------------------:|
-| Yi-6B | 15 GB | RTX3090
RTX4090
A10
A30 |
+| Yi-6B | 15 GB | 1 x RTX 3090
1 x RTX 4090
A10
A30 |
| Yi-6B-200K | 50 GB | A800 (80 GB) |
| Yi-9B | 20 GB | 1 x RTX 4090 (24 GB) |
| Yi-34B | 72 GB | 4 x RTX 4090
A800 (80 GB) |
@@ -1012,6 +1012,8 @@ With all these resources at your fingertips, you're ready to start your exciting
- [Benchmarks](#benchmarks)
- [Chat model performance](#chat-model-performance)
- [Base model performance](#base-model-performance)
+ - [Yi-34B and Yi-34B-200K](#yi-34b-and-yi-34b-200k)
+ - [Yi-9B](#yi-9b)
## Ecosystem
@@ -1020,8 +1022,8 @@ Yi has a comprehensive ecosystem, offering a range of tools, services, and model
- [Upstream](#upstream)
- [Downstream](#downstream)
- [Serving](#serving)
- - [Quantitation](#️quantitation)
- - [Fine-tuning](#️fine-tuning)
+ - [Quantization](#quantization-1)
+ - [Fine-tuning](#fine-tuning-1)
- [API](#api)
### Upstream
@@ -1146,7 +1148,7 @@ Yi-9B is almost the best among a range of similar-sized open-source models (incl
![Yi-9B benchmark - details](https://github.com/01-ai/Yi/blob/main/assets/img/Yi-9B_benchmark_details.png?raw=true)
-- In terms of **overall** ability (`Mean-All), Yi-9B performs the best among similarly sized open-source models, surpassing DeepSeek-Coder, DeepSeek-Math, Mistral-7B, SOLAR-10.7B, and Gemma-7B.
+- In terms of **overall** ability (Mean-All), Yi-9B performs the best among similarly sized open-source models, surpassing DeepSeek-Coder, DeepSeek-Math, Mistral-7B, SOLAR-10.7B, and Gemma-7B.
![Yi-9B benchmark - overall](https://github.com/01-ai/Yi/blob/main/assets/img/Yi-9B_benchmark_overall.png?raw=true)