Ateeqq commited on
Commit
4e253e9
·
verified ·
1 Parent(s): 1dc8986

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +12 -7
README.md CHANGED
@@ -1,26 +1,31 @@
1
  ---
2
- license: llama3
3
  inference:
4
  parameters:
5
  num_beams: 3
6
  num_beam_groups: 3
7
  num_return_sequences: 1
8
- repetition_penalty: 3.0
9
  diversity_penalty: 3.01
10
  no_repeat_ngram_size: 2
11
  temperature: 0.8
12
  max_length: 64
13
  widget:
14
  - text: >-
15
- paraphraser: Learn to build generative AI applications with an expert AWS instructor with the 2-day Developing Generative AI Applications on AWS course.
 
 
16
  example_title: AWS course
17
  - text: >-
18
- paraphraser: In healthcare, Generative AI can help generate synthetic medical data to train machine learning models, develop new drug candidates, and design clinical trials.
 
 
19
  example_title: Generative AI
20
  - text: >-
21
- paraphraser: By leveraging prior model training through transfer learning, fine-tuning
22
- can reduce the amount of expensive computing power and labeled data needed
23
- to obtain large models tailored to niche use cases and business needs.
 
24
  example_title: Fine Tuning
25
  extra_gated_fields:
26
  geo: ip_location
 
1
  ---
2
+ license: openrail
3
  inference:
4
  parameters:
5
  num_beams: 3
6
  num_beam_groups: 3
7
  num_return_sequences: 1
8
+ repetition_penalty: 3
9
  diversity_penalty: 3.01
10
  no_repeat_ngram_size: 2
11
  temperature: 0.8
12
  max_length: 64
13
  widget:
14
  - text: >-
15
+ paraphraser: Learn to build generative AI applications with an expert AWS
16
+ instructor with the 2-day Developing Generative AI Applications on AWS
17
+ course.
18
  example_title: AWS course
19
  - text: >-
20
+ paraphraser: In healthcare, Generative AI can help generate synthetic
21
+ medical data to train machine learning models, develop new drug candidates,
22
+ and design clinical trials.
23
  example_title: Generative AI
24
  - text: >-
25
+ paraphraser: By leveraging prior model training through transfer learning,
26
+ fine-tuning can reduce the amount of expensive computing power and labeled
27
+ data needed to obtain large models tailored to niche use cases and business
28
+ needs.
29
  example_title: Fine Tuning
30
  extra_gated_fields:
31
  geo: ip_location