Update pip install instructions, bump to 0.2

README.md

@@ -24,9 +24,14 @@ and experiment with. The notations in the Triton implementation are also closer
 to what's used in our paper.
 
 
-## Alpha release (0.1).
+## Beta release (0.2).
 
-To compile (requiring CUDA 11, NVCC, and an Turing or Ampere GPU):
+To install (requiring CUDA 11, NVCC, and an Turing or Ampere GPU):
+```sh
+pip install flash-attn
+```
+
+Alternatively you can compile from source:
 ```
 python setup.py install
 ```
@@ -44,7 +49,7 @@ FlashAttention currently supports:
 3. Head dimensions that are multiples of 8, up to 128 (e.g., 8, 16, 24, ..., 128). Head dim > 64 backward requires A100.
 
 Our tentative roadmap:
-1. [Jun 2022] Make package pip-installable.
+1. ~~[Jun 2022] Make package pip-installable~~[Done, thanks to lucidrains].
 2. ~~[Jun 2022] Support SM86 GPUs (e.g., RTX 3080, 3090)~~[Done].
 3. [Jun 2022] Refactor to use Cutlass.
 4. ~~[Jun 2022] Support SM75 GPUs (e.g. T4)~~[Done].

setup.py

@@ -152,7 +152,7 @@ ext_modules.append(
 
 setup(
     name="flash_attn",
-    version="0.1",
+    version="0.2",
     packages=find_packages(
         exclude=("build", "csrc", "include", "tests", "dist", "docs", "benchmarks", "flash_attn.egg-info",)
     ),
@@ -164,7 +164,7 @@ setup(
     url="https://github.com/HazyResearch/flash-attention",
     classifiers=[
         "Programming Language :: Python :: 3",
-        "License :: OSI Approved :: Apache Software License",
+        "License :: OSI Approved :: BSD License",
         "Operating System :: Unix",
     ],
     ext_modules=ext_modules,