Unverified Commit b5afe229 authored by DongGeon Lee's avatar DongGeon Lee Committed by GitHub
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Fix outdated links to the latest links in `docs` (#1876)

parent 5711ab87
...@@ -10,7 +10,7 @@ Equivalently, running the library can be done via the `lm-eval` entrypoint at th ...@@ -10,7 +10,7 @@ Equivalently, running the library can be done via the `lm-eval` entrypoint at th
This mode supports a number of command-line arguments, the details of which can be also be seen via running with `-h` or `--help`: This mode supports a number of command-line arguments, the details of which can be also be seen via running with `-h` or `--help`:
- `--model` : Selects which model type or provider is evaluated. Must be a string corresponding to the name of the model type/provider being used. See [the main README](https://github.com/EleutherAI/lm-evaluation-harness/tree/main#commercial-apis) for a full list of enabled model names and supported libraries or APIs. - `--model` : Selects which model type or provider is evaluated. Must be a string corresponding to the name of the model type/provider being used. See [the main README](https://github.com/EleutherAI/lm-evaluation-harness/tree/main#model-apis-and-inference-servers) for a full list of enabled model names and supported libraries or APIs.
- `--model_args` : Controls parameters passed to the model constructor. Accepts a string containing comma-separated keyword arguments to the model class of the format `"arg1=val1,arg2=val2,..."`, such as, for example `--model_args pretrained=EleutherAI/pythia-160m,dtype=float32`. For a full list of what keyword arguments, see the initialization of the `lm_eval.api.model.LM` subclass, e.g. [`HFLM`](https://github.com/EleutherAI/lm-evaluation-harness/blob/365fcda9b85bbb6e0572d91976b8daf409164500/lm_eval/models/huggingface.py#L66) - `--model_args` : Controls parameters passed to the model constructor. Accepts a string containing comma-separated keyword arguments to the model class of the format `"arg1=val1,arg2=val2,..."`, such as, for example `--model_args pretrained=EleutherAI/pythia-160m,dtype=float32`. For a full list of what keyword arguments, see the initialization of the `lm_eval.api.model.LM` subclass, e.g. [`HFLM`](https://github.com/EleutherAI/lm-evaluation-harness/blob/365fcda9b85bbb6e0572d91976b8daf409164500/lm_eval/models/huggingface.py#L66)
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...@@ -35,7 +35,7 @@ and rename the folders and YAML file(s) as desired. ...@@ -35,7 +35,7 @@ and rename the folders and YAML file(s) as desired.
### Selecting and configuring a dataset ### Selecting and configuring a dataset
All data downloading and management is handled through the HuggingFace (**HF**) [`datasets`](https://github.com/huggingface/datasets) API. So, the first thing you should do is check to see if your task's dataset is already provided in their catalog [here](https://huggingface.co/datasets). If it's not in there, please consider adding it to their Hub to make it accessible to a wider user base by following their [new dataset guide](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md) All data downloading and management is handled through the HuggingFace (**HF**) [`datasets`](https://github.com/huggingface/datasets) API. So, the first thing you should do is check to see if your task's dataset is already provided in their catalog [here](https://huggingface.co/datasets). If it's not in there, please consider adding it to their Hub to make it accessible to a wider user base by following their [new dataset guide](https://github.com/huggingface/datasets/blob/main/ADD_NEW_DATASET.md)
. .
Once you have a HuggingFace dataset prepared for your task, we want to assign our new YAML to use this dataset: Once you have a HuggingFace dataset prepared for your task, we want to assign our new YAML to use this dataset:
...@@ -213,7 +213,7 @@ def wikitext_detokenizer(doc): ...@@ -213,7 +213,7 @@ def wikitext_detokenizer(doc):
return string return string
``` ```
We can load this function in `doc_to_target` by using a `!function` operator after `doc_to_target` and followed by `<file name>.<function name>`. In the file [wikitext.yaml](https://github.com/EleutherAI/lm-evaluation-harness/blob/6ae376e3a43caa58b95bb8aa73054a94827bf560/lm_eval/tasks/wikitext/wikitext.yaml) we write: We can load this function in `doc_to_target` by using a `!function` operator after `doc_to_target` and followed by `<file name>.<function name>`. In the file [wikitext.yaml](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/lm_eval/tasks/wikitext/wikitext.yaml) we write:
``` ```
doc_to_target: !function preprocess_wikitext.wikitext_detokenizer doc_to_target: !function preprocess_wikitext.wikitext_detokenizer
``` ```
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...@@ -190,7 +190,7 @@ You can base a YAML on another YAML file as a template. This can be handy when y ...@@ -190,7 +190,7 @@ You can base a YAML on another YAML file as a template. This can be handy when y
include: <YAML filename or with full path> include: <YAML filename or with full path>
... ...
``` ```
You can find an example of how to use this feature at [gsm8k-cot-self-consistency.yaml](https://github.com/EleutherAI/lm-evaluation-harness/blob/3c07cc04a92fc467d7c9a94894aeddd58c93a5da/lm_eval/tasks/gsm8k/gsm8k-cot-self-consistency.yaml) where it is based off [gsm8k-cot.yaml](https://github.com/EleutherAI/lm-evaluation-harness/blob/3c07cc04a92fc467d7c9a94894aeddd58c93a5da/lm_eval/tasks/gsm8k/gsm8k-cot.yaml) You can find an example of how to use this feature at [gsm8k-cot-self-consistency.yaml](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/lm_eval/tasks/gsm8k/gsm8k-cot-self-consistency.yaml) where it is based off [gsm8k-cot.yaml](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/lm_eval/tasks/gsm8k/gsm8k-cot.yaml)
## Passing Arguments to Metrics ## Passing Arguments to Metrics
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