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fix: align readme with current mteb #1493

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fix: align readme with current mteb #1493

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10 changes: 8 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -50,6 +50,8 @@ model_name = "average_word_embeddings_komninos"
# model_name = "sentence-transformers/all-MiniLM-L6-v2"

model = SentenceTransformer(model_name)
# or directly from mteb:
model = mteb.get_model(model_name)
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Should we just recommend this one always?

and maybe rephrase to:

Suggested change
model = mteb.get_model(model_name)
model = mteb.get_model(model_name) # if the model is not implemented in MTEB it will be eq. to SentenceTransformer(model_name)

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Yes, but I'm not sure removing it is the best approach. I can make changes to whatever you think is better

tasks = mteb.get_tasks(tasks=["Banking77Classification"])
evaluation = mteb.MTEB(tasks=tasks)
results = evaluation.run(model, output_folder=f"results/{model_name}")
Expand Down Expand Up @@ -220,9 +222,13 @@ Note that the public leaderboard uses the test splits for all datasets except MS
Models should implement the following interface, implementing an `encode` function taking as inputs a list of sentences, and returning a list of embeddings (embeddings can be `np.array`, `torch.tensor`, etc.). For inspiration, you can look at the [mteb/mtebscripts repo](https://github.com/embeddings-benchmark/mtebscripts) used for running diverse models via SLURM scripts for the paper.

```python
import mteb
from mteb.encoder_interface import PromptType
from mteb.models.wrapper import Wrapper
import numpy as np


class CustomModel:
class CustomModel(Wrapper):
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Why does it need to inherit from wrapper? I would instead inherit from the Encoder protocol

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@Samoed Samoed Nov 24, 2024 •
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MTEB class will wrap models that do not inherit from the wrapper class.

mteb/mteb/evaluation/MTEB.py

Lines 366 to 367 in 3ff38ec

if not isinstance(model, Wrapper):
model = SentenceTransformerWrapper(model)

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@KennethEnevoldsen KennethEnevoldsen Nov 24, 2024 •
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Hmm, shouldn't it just wrap SentenceTransformers?

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It can be like this. You changed it in mieb

mteb/mteb/evaluation/MTEB.py

Lines 356 to 357 in fab0b82

if isinstance(model, (SentenceTransformer, CrossEncoder)):
model = SentenceTransformerWrapper(model)
I can change there too

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Hmm then it will also be merged into v2.0.0 in which case we should probably just update the readme there (I plan to merge it during December)

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So, for now I think this PR can be merged, and I will update readme in the 2.0 branch

def encode(
self,
sentences: list[str],
Expand All @@ -244,7 +250,7 @@ class CustomModel:
pass

model = CustomModel()
tasks = mteb.get_task("Banking77Classification")
tasks = mteb.get_tasks(tasks=["Banking77Classification"])
evaluation = MTEB(tasks=tasks)
evaluation.run(model)
```
Expand Down