phoenix/litellm
1
0
Fork 0
forked from phoenix/litellm-mirror
Code Pull requests Activity

(docs) lm harness

Browse source
This commit is contained in:
ishaan-jaff 2023-11-16 14:21:37 -08:00
parent d7f7694848
commit 8d0f4bfc74
1 changed files with 25 additions and 3 deletions
Download patch file Download diff file Expand all files Collapse all files

28
docs/my-website/docs/tutorials/lm_evaluation_harness.md
View file

@ -8,6 +8,8 @@ Evaluate LLMs 20x faster with TGI via litellm proxy's `/completions` endpoint.
This tutorial assumes you're using the `big-refactor` branch of [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness/tree/big-refactor)
NOTE: LM Harness has not updated to using `openai 1.0.0+`, in order to deal with this we will run lm harness in a venv
**Step 1: Start the local proxy**
see supported models [here](https://docs.litellm.ai/docs/simple_proxy)
```shell
@ -20,10 +22,22 @@ Using a custom api base
$ export HUGGINGFACE_API_KEY=my-api-key #[OPTIONAL]
$ litellm --model huggingface/tinyllama --api_base https://k58ory32yinf1ly0.us-east-1.aws.endpoints.huggingface.cloud
```
OpenAI Compatible Endpoint at http://0.0.0.0:8000
**Step 2: Set OpenAI API Base & Key**
**Step 2: Create a Virtual Env for LM Harness + Use OpenAI 0.28.1**
We will now run lm harness with a new virtual env with openai==0.28.1
```shell
python3 -m venv lmharness
source lmharness/bin/activate
```
Pip install openai==0.28.01 in the venv
```shell
pip install openai==0.28.01
```
**Step 3: Set OpenAI API Base & Key**
```shell
$ export OPENAI_API_BASE=http://0.0.0.0:8000
```
@ -33,7 +47,15 @@ LM Harness requires you to set an OpenAI API key `OPENAI_API_SECRET_KEY` for run
export OPENAI_API_SECRET_KEY=anything
```
**Step 3: Run LM-Eval-Harness**
**Step 4: Run LM-Eval-Harness**
```shell
cd lm-evaluation-harness
```
pip install lm harness dependencies in venv
```
python3 -m pip install -e .
```
```shell
python3 -m lm_eval \