nunonmg commited on
Commit
3ce0db8
1 Parent(s): 1739212

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +4 -3
README.md CHANGED
@@ -22,7 +22,7 @@ pipeline_tag: translation
22
  ### Model Description
23
 
24
  TowerInstruct-7B is a language model that results from fine-tuning TowerBase on the TowerBlocks supervised fine-tuning dataset. TowerInstruct-7B-v0.1 is the first model in the series.
25
- The model is trained to handle several translation-related tasks, such as general machine translation (e.g., sentence- and document-level translation, terminology-aware translation, context-aware translation), automatic post edition, named-entity recognition, gramatical error correction, and paraphrase generation.
26
  We will release more details in the upcoming technical report.
27
 
28
  - **Developed by:** Unbabel, Instituto Superior Técnico, CentraleSupélec University of Paris-Saclay
@@ -34,7 +34,7 @@ We will release more details in the upcoming technical report.
34
  ## Intended uses & limitations
35
 
36
  The model was initially fine-tuned on a filtered and preprocessed supervised fine-tuning dataset ([TowerBlocks](https://huggingface.co/datasets/Unbabel/TowerBlocks-v0.1)), which contains a diverse range of data sources:
37
- - Translation
38
  - Automatic Post Edition
39
  - Machine Translation Evaluation
40
  - Context-aware Translation
@@ -75,7 +75,8 @@ print(outputs[0]["generated_text"])
75
 
76
  ### Out-of-Scope Use
77
 
78
- The model is not guaranteed to perform for languages other than the 10 languages it supports. Even though we trained the model on conversational data and code instructions, it is not intended to be used as a conversational chatbot or code assistant.
 
79
 
80
  ## Bias, Risks, and Limitations
81
 
 
22
  ### Model Description
23
 
24
  TowerInstruct-7B is a language model that results from fine-tuning TowerBase on the TowerBlocks supervised fine-tuning dataset. TowerInstruct-7B-v0.1 is the first model in the series.
25
+ The model is trained to handle several translation-related tasks, such as general machine translation (e.g., sentence- and paragraph-level translation, terminology-aware translation, context-aware translation), automatic post edition, named-entity recognition, gramatical error correction, and paraphrase generation.
26
  We will release more details in the upcoming technical report.
27
 
28
  - **Developed by:** Unbabel, Instituto Superior Técnico, CentraleSupélec University of Paris-Saclay
 
34
  ## Intended uses & limitations
35
 
36
  The model was initially fine-tuned on a filtered and preprocessed supervised fine-tuning dataset ([TowerBlocks](https://huggingface.co/datasets/Unbabel/TowerBlocks-v0.1)), which contains a diverse range of data sources:
37
+ - Translation (sentence and paragraph-level)
38
  - Automatic Post Edition
39
  - Machine Translation Evaluation
40
  - Context-aware Translation
 
75
 
76
  ### Out-of-Scope Use
77
 
78
+ The model is not guaranteed to perform for languages other than the 10 languages it supports. Even though we trained the model on conversational data and code instructions, it is not intended to be used as a conversational chatbot or code assistant.
79
+ We are currently working on improving quality and consistency on document-level translation. This model should is not intended to be use as a document-level translator.
80
 
81
  ## Bias, Risks, and Limitations
82