Archives/petals
2
0
Fork 0
mirror of https://github.com/bigscience-workshop/petals synced 2024-10-31 09:20:41 +00:00
Code Issues Packages Projects Releases Wiki Activity

Small text fixes

Browse Source
This commit is contained in:
Artem Chumachenko 2022-11-07 13:37:55 +04:00
parent 52a142ba43
commit 749a498c1f
3 changed files with 12 additions and 14 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@ -155,7 +155,7 @@ loss.backward()
print("Gradients (norm):", model.transformer.word_embeddings.weight.grad.norm())
```
Of course, this is a simplified code snippet. For actual training, see our example on "deep" prompt-tuning here.
Of course, this is a simplified code snippet. For actual training, see the example notebooks with "deep" prompt-tuning:
- Simple text semantic classification: [examples/prompt-tuning-sst2.ipynb](./examples/prompt-tuning-sst2.ipynb).
- A personified chatbot: [examples/prompt-tuning-personachat.ipynb](./examples/prompt-tuning-personachat.ipynb).

15
examples/prompt-tuning-personachat.ipynb
View File

@ -33,7 +33,6 @@
"metadata": {},
"outputs": [],
"source": [
"# This block is only need for colab users. It will change nothing if you are running this notebook locally.\n",
"import subprocess\n",
"import sys\n",
"\n",
@ -41,14 +40,14 @@
"IN_COLAB = 'google.colab' in sys.modules\n",
"\n",
"if IN_COLAB:\n",
" subprocess.run(['git', 'clone', 'https://github.com/bigscience-workshop/petals'])\n",
" subprocess.run(['pip', 'install', '-r', 'petals/requirements.txt'])\n",
" subprocess.run(['pip', 'install', 'datasets', 'lib64'])\n",
" subprocess.run(\"git clone https://github.com/bigscience-workshop/petals\", shell=True)\n",
" subprocess.run(\"pip install -r petals/requirements.txt\", shell=True)\n",
" subprocess.run(\"pip install datasets wandb\", shell=True)\n",
"\n",
" try:\n",
" subprocess.check_output([\"nvidia-smi\", \"-L\"])\n",
" except subprocess.CalledProcessError as e:\n",
" subprocess.run(['rm', '-r', '/usr/local/cuda/lib64'])\n",
" subprocess.run(\"rm -r /usr/local/cuda/lib64\", shell=True)\n",
"\n",
" sys.path.insert(0, './petals/')\n",
"else:\n",
@ -315,7 +314,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.8.10 64-bit",
"display_name": "Python 3.8.0 ('petals')",
"language": "python",
"name": "python3"
},
@ -329,11 +328,11 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.9"
"version": "3.8.0"
},
"vscode": {
"interpreter": {
"hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
"hash": "a303c9f329a09f921588ea6ef03898c90b4a8e255a47e0bd6e36f6331488f609"
}
}
},

9
examples/prompt-tuning-sst2.ipynb
View File

@ -33,7 +33,6 @@
"metadata": {},
"outputs": [],
"source": [
"# This block is only need for colab users. It will change nothing if you are running this notebook locally.\n",
"import subprocess\n",
"import sys\n",
"\n",
@ -41,14 +40,14 @@
"IN_COLAB = 'google.colab' in sys.modules\n",
"\n",
"if IN_COLAB:\n",
" subprocess.run(['git', 'clone', 'https://github.com/bigscience-workshop/petals'])\n",
" subprocess.run(['pip', 'install', '-r', 'petals/requirements.txt'])\n",
" subprocess.run(['pip', 'install', 'datasets', 'lib64'])\n",
" subprocess.run(\"git clone https://github.com/bigscience-workshop/petals\", shell=True)\n",
" subprocess.run(\"pip install -r petals/requirements.txt\", shell=True)\n",
" subprocess.run(\"pip install datasets wandb\", shell=True)\n",
"\n",
" try:\n",
" subprocess.check_output([\"nvidia-smi\", \"-L\"])\n",
" except subprocess.CalledProcessError as e:\n",
" subprocess.run(['rm', '-r', '/usr/local/cuda/lib64'])\n",
" subprocess.run(\"rm -r /usr/local/cuda/lib64\", shell=True)\n",
"\n",
" sys.path.insert(0, './petals/')\n",
"else:\n",