Update README.md (#938)
This commit is contained in:
Daniel Han
GitHub
parent
861f232047
commit
0927c34392
1 changed files with 44 additions and 61 deletions
105
README.md
105
README.md
|
|
@ -94,85 +94,68 @@ All notebooks are **beginner friendly**! Add your dataset, click "Run All", and
|
|||
|
||||
## 💾 Installation Instructions
|
||||
|
||||
If you have Pytorch 2.3 and CUDA 12.1, install Unsloth with `pip install unsloth[colab-new]` then `pip install --no-deps "xformers<0.0.27" "trl<0.9.0" peft accelerate bitsandbytes`
|
||||
|
||||
### Conda Installation
|
||||
Select either `pytorch-cuda=11.8` for CUDA 11.8 or `pytorch-cuda=12.1` for CUDA 12.1. If you have `mamba`, use `mamba` instead of `conda` for faster solving. See this [Github issue](https://github.com/unslothai/unsloth/issues/73) for help on debugging Conda installs.
|
||||
`⚠️Only use Conda if you have it. If not, use Pip`. Select either `pytorch-cuda=11.8,12.1` for CUDA 11.8 or CUDA 12.1. If you have `mamba`, use `mamba` instead of `conda` for faster solving. We support `python=3.10,3.11,3.12`.
|
||||
```bash
|
||||
conda create --name unsloth_env \
|
||||
python=3.10 \
|
||||
pytorch-cuda=<11.8/12.1> \
|
||||
python=3.11 \
|
||||
pytorch-cuda=12.1 \
|
||||
pytorch cudatoolkit xformers -c pytorch -c nvidia -c xformers \
|
||||
-y
|
||||
conda activate unsloth_env
|
||||
|
||||
pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
|
||||
|
||||
pip install --no-deps "trl<0.9.0" peft accelerate bitsandbytes
|
||||
pip install --no-deps trl peft accelerate bitsandbytes
|
||||
```
|
||||
|
||||
<details>
|
||||
<summary>If you're looking to install Conda in a Linux environment, <a href="https://docs.anaconda.com/miniconda/">read here</a>, or run the below 🔽</summary>
|
||||
|
||||
```bash
|
||||
mkdir -p ~/miniconda3
|
||||
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
|
||||
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
|
||||
rm -rf ~/miniconda3/miniconda.sh
|
||||
~/miniconda3/bin/conda init bash
|
||||
~/miniconda3/bin/conda init zsh
|
||||
```
|
||||
</details>
|
||||
|
||||
### Pip Installation
|
||||
Do **NOT** use this if you have Anaconda. You must use the Conda install method, or else stuff will BREAK.
|
||||
`⚠️Do **NOT** use this if you have Conda.` Pip is a bit more complex since there are dependency issues. The pip command is different for `torch 2.2,2.3,2.4` and CUDA versions.
|
||||
|
||||
1. Find your CUDA version via
|
||||
```python
|
||||
import torch; torch.version.cuda
|
||||
```
|
||||
2. For Pytorch 2.1.0: You can update Pytorch via Pip (interchange `cu121` / `cu118`). Go to https://pytorch.org/ to learn more. Select either `cu118` for CUDA 11.8 or `cu121` for CUDA 12.1. If you have a RTX 3060 or higher (A100, H100 etc), use the `"ampere"` path. For Pytorch 2.1.1: go to step 3. For Pytorch 2.2.0: go to step 4.
|
||||
```bash
|
||||
pip install --upgrade --force-reinstall --no-cache-dir torch==2.1.0 triton \
|
||||
--index-url https://download.pytorch.org/whl/cu121
|
||||
```
|
||||
```bash
|
||||
pip install "unsloth[cu118] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu118-ampere] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121-ampere] @ git+https://github.com/unslothai/unsloth.git"
|
||||
```
|
||||
3. For Pytorch 2.1.1: Use the `"ampere"` path for newer RTX 30xx GPUs or higher.
|
||||
```bash
|
||||
pip install --upgrade --force-reinstall --no-cache-dir torch==2.1.1 triton \
|
||||
--index-url https://download.pytorch.org/whl/cu121
|
||||
```
|
||||
```bash
|
||||
pip install "unsloth[cu118-torch211] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121-torch211] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu118-ampere-torch211] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121-ampere-torch211] @ git+https://github.com/unslothai/unsloth.git"
|
||||
```
|
||||
4. For Pytorch 2.2.0: Use the `"ampere"` path for newer RTX 30xx GPUs or higher.
|
||||
```bash
|
||||
pip install --upgrade --force-reinstall --no-cache-dir torch==2.2.0 triton \
|
||||
--index-url https://download.pytorch.org/whl/cu121
|
||||
```
|
||||
```bash
|
||||
pip install "unsloth[cu118-torch220] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121-torch220] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu118-ampere-torch220] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121-ampere-torch220] @ git+https://github.com/unslothai/unsloth.git"
|
||||
```
|
||||
5. If you get errors, try the below first, then go back to step 1:
|
||||
In general, if you have `torch 2.4` and `CUDA 12.1`, use:
|
||||
```bash
|
||||
pip install --upgrade pip
|
||||
pip install "unsloth[cu121-torch240] @ git+https://github.com/unslothai/unsloth.git"
|
||||
```
|
||||
6. For Pytorch 2.2.1:
|
||||
```bash
|
||||
# RTX 3090, 4090 Ampere GPUs:
|
||||
pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install --no-deps packaging ninja einops flash-attn xformers trl peft accelerate bitsandbytes
|
||||
|
||||
# Pre Ampere RTX 2080, T4, GTX 1080 GPUs:
|
||||
pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install --no-deps xformers "trl<0.9.0" peft accelerate bitsandbytes
|
||||
```
|
||||
7. For Pytorch 2.3.0: Use the `"ampere"` path for newer RTX 30xx GPUs or higher.
|
||||
Or, run the below in a terminal to get the optional pip installation command:
|
||||
```bash
|
||||
pip install "unsloth[cu118-torch230] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121-torch230] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu118-ampere-torch230] @ git+https://github.com/unslothai/unsloth.git"
|
||||
pip install "unsloth[cu121-ampere-torch230] @ git+https://github.com/unslothai/unsloth.git"
|
||||
wget -qO- https://raw.githubusercontent.com/unslothai/unsloth/main/unsloth/_auto_install.py | python -
|
||||
```
|
||||
8. To troubleshoot installs try the below (all must succeed). Xformers should mostly all be available.
|
||||
|
||||
Or, run the below manually in a Python REPL:
|
||||
```python
|
||||
try: import torch
|
||||
except: raise ImportError("Install torch via `pip install torch`")
|
||||
from packaging.version import Version as V
|
||||
v = V(torch.__version__)
|
||||
cuda = str(torch.version.cuda)
|
||||
is_ampere = torch.cuda.get_device_capability()[0] >= 8
|
||||
if cuda != "12.1" and cuda != "11.8": raise RuntimeError(f"CUDA = {cuda} not supported!")
|
||||
if v <= V('2.1.0'): raise RuntimeError(f"Torch = {v} too old!")
|
||||
elif v <= V('2.1.1'): x = 'cu{}{}-torch211'
|
||||
elif v <= V('2.1.2'): x = 'cu{}{}-torch212'
|
||||
elif v < V('2.3.0'): x = 'cu{}{}-torch220'
|
||||
elif v < V('2.4.0'): x = 'cu{}{}-torch230'
|
||||
elif v < V('2.5.0'): x = 'cu{}{}-torch240'
|
||||
else: raise RuntimeError(f"Torch = {v} too new!")
|
||||
x = x.format(cuda.replace(".", ""), "-ampere" if is_ampere else "")
|
||||
print(f'pip install --upgrade pip && pip install "unsloth[{x}] @ git+https://github.com/unslothai/unsloth.git"')
|
||||
```
|
||||
|
||||
Afterwards, confirm if `nvcc` `xformers` and `bitsandbytes` have successfully installed - if not, install them individually first until they work, then install Unsloth.
|
||||
```bash
|
||||
nvcc
|
||||
python -m xformers.info
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue