Clémentine commited on
Commit
eaace79
1 Parent(s): bb149ba

Simplify About

Browse files
Files changed (1) hide show
  1. src/display/about.py +6 -8
src/display/about.py CHANGED
@@ -10,15 +10,17 @@ The leaderboard's backend runs the great [Eleuther AI Language Model Evaluation
10
  """
11
 
12
  LLM_BENCHMARKS_TEXT = f"""
 
 
13
  # Context
14
  With the plethora of large language models (LLMs) and chatbots being released week upon week, often with grandiose claims of their performance, it can be hard to filter out the genuine progress that is being made by the open-source community and which model is the current state of the art.
15
 
16
  ## Icons
17
- {ModelType.PT.to_str(" : ")} model: new, base models, trained on a given corpora
18
- {ModelType.FT.to_str(" : ")} model: pretrained models finetuned on more data
19
  Specific fine-tune subcategories (more adapted to chat):
20
- {ModelType.IFT.to_str(" : ")} model: instruction fine-tunes, which are model fine-tuned specifically on datasets of task instruction
21
- {ModelType.RL.to_str(" : ")} model: reinforcement fine-tunes, which usually change the model loss a bit with an added policy.
22
  If there is no icon, we have not uploaded the information on the model yet, feel free to open an issue with the model information!
23
 
24
  "Flagged" indicates that this model has been flagged by the community, and should probably be ignored! Clicking the link will redirect you to the discussion about the model.
@@ -71,10 +73,6 @@ Side note on the baseline scores:
71
  To get more information about quantization, see:
72
  - 8 bits: [blog post](https://huggingface.co/blog/hf-bitsandbytes-integration), [paper](https://arxiv.org/abs/2208.07339)
73
  - 4 bits: [blog post](https://huggingface.co/blog/4bit-transformers-bitsandbytes), [paper](https://arxiv.org/abs/2305.14314)
74
-
75
- ## More resources
76
- If you still have questions, you can check our FAQ [here](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/179)!
77
- We also gather cool resources from the community, other teams, and other labs [here](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/174)!
78
  """
79
 
80
  EVALUATION_QUEUE_TEXT = """
 
10
  """
11
 
12
  LLM_BENCHMARKS_TEXT = f"""
13
+ Useful links: [FAQ](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/179), [Community resources](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/174), [Collection of best models](https://huggingface.co/collections/open-llm-leaderboard/llm-leaderboard-best-models-652d6c7965a4619fb5c27a03).
14
+
15
  # Context
16
  With the plethora of large language models (LLMs) and chatbots being released week upon week, often with grandiose claims of their performance, it can be hard to filter out the genuine progress that is being made by the open-source community and which model is the current state of the art.
17
 
18
  ## Icons
19
+ - {ModelType.PT.to_str(" : ")} model: new, base models, trained on a given corpora
20
+ - {ModelType.FT.to_str(" : ")} model: pretrained models finetuned on more data
21
  Specific fine-tune subcategories (more adapted to chat):
22
+ - {ModelType.IFT.to_str(" : ")} model: instruction fine-tunes, which are model fine-tuned specifically on datasets of task instruction
23
+ - {ModelType.RL.to_str(" : ")} model: reinforcement fine-tunes, which usually change the model loss a bit with an added policy.
24
  If there is no icon, we have not uploaded the information on the model yet, feel free to open an issue with the model information!
25
 
26
  "Flagged" indicates that this model has been flagged by the community, and should probably be ignored! Clicking the link will redirect you to the discussion about the model.
 
73
  To get more information about quantization, see:
74
  - 8 bits: [blog post](https://huggingface.co/blog/hf-bitsandbytes-integration), [paper](https://arxiv.org/abs/2208.07339)
75
  - 4 bits: [blog post](https://huggingface.co/blog/4bit-transformers-bitsandbytes), [paper](https://arxiv.org/abs/2305.14314)
 
 
 
 
76
  """
77
 
78
  EVALUATION_QUEUE_TEXT = """