alpeshsonar
commited on
Commit
•
508eeed
1
Parent(s):
37ef975
Update README.md
Browse files
README.md
CHANGED
@@ -1,17 +1,52 @@
|
|
1 |
---
|
2 |
-
language:
|
3 |
- en
|
4 |
widget:
|
5 |
-
- text:
|
6 |
-
|
7 |
-
|
8 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
9 |
library_name: transformers
|
10 |
tags:
|
11 |
- lot
|
12 |
- line of therapy
|
13 |
license: apache-2.0
|
14 |
pipeline_tag: text2text-generation
|
|
|
15 |
---
|
16 |
## Uses
|
17 |
|
@@ -27,4 +62,4 @@ input_text = """"Extract lots from given text.
|
|
27 |
input_ids = tokenizer(input_text, return_tensors="pt").input_ids
|
28 |
outputs = model.generate(input_ids,max_new_tokens=1024)
|
29 |
print(tokenizer.decode(outputs[0],skip_special_tokens=True))
|
30 |
-
```
|
|
|
1 |
---
|
2 |
+
language:
|
3 |
- en
|
4 |
widget:
|
5 |
+
- text: >-
|
6 |
+
Extract lots from given text.
|
7 |
+
|
8 |
+
1. Age 18 to 75 years, inclusive. 2. Study participants must have a
|
9 |
+
diagnosis of symptomatic multiple myeloma requiring systemic therapy and are
|
10 |
+
eligible for the planned ASCT. 3. Untreated bone marrow sample was shipped
|
11 |
+
to Princess Margaret Hospital for MRD assay. 4. Must have been treated with
|
12 |
+
a velcade-based induction regimen. No limit to the number of cycles of
|
13 |
+
induction. 5. Study participants in whom the minimum stem cell dose of 2.0 x
|
14 |
+
106 cluster of differentiation (CD)34+ cells/kg has been collected. 6.
|
15 |
+
Eastern Cooperative Oncology Group (ECOG) Performance Status of 0-2. 7.
|
16 |
+
Negative beta-human chorionic gonadotropin (β-HCG) pregnancy test in all
|
17 |
+
females of child-bearing potential (FOCBP). 8. Ability to provide written
|
18 |
+
informed consent prior to initiation of any study-related procedures, and
|
19 |
+
ability, in the opinion of the Principal Investigator, to comply with all
|
20 |
+
requirements of the study.
|
21 |
+
example_title: Translation
|
22 |
+
- text: >-
|
23 |
+
Extract lots from given text.
|
24 |
+
|
25 |
+
age ≥18 years * patients with de novo or secondary AML, with an unfavorable
|
26 |
+
or intermediate karyotype (according to the 2017 ELN classification), or
|
27 |
+
patients with relapsing AML who may receive second-line treatment * not
|
28 |
+
candidates for intensive induction, for the following reasons* 75 years or ≥
|
29 |
+
18 to 74 years and at least one of the following comorbidities: PS ≥ 2 or a
|
30 |
+
history of heart failure requiring treatment or LVEF ≤ 50% or chronic stable
|
31 |
+
angina or FEV1 ≤ 65% or DLCO ≤ 65% or creatinine clearance <45 ml / min; or
|
32 |
+
liver damage with total bilirubin> 1.5 N or other comorbidities that the
|
33 |
+
hematologist considers incompatible with intensive treatment * ineligible
|
34 |
+
for a classic allogeneic hematopoietic stem cell transplant due to the
|
35 |
+
presence of co-morbidities or too high a risk of toxicity >70 years old or
|
36 |
+
at least one of the following comorbidities: PS ≥ 2 or a history of heart
|
37 |
+
failure requiring treatment or LVEF ≤ 50% or chronic stable angina or FEV1 ≤
|
38 |
+
65% or DLCO ≤ 65% or creatinine clearance <45 ml / min; or liver damage with
|
39 |
+
total bilirubin> 1.5 N * may receive chemotherapy with hypomethylating
|
40 |
+
agents have a partially compatible (haplo-identical) major family donor (≥18
|
41 |
+
years old) eligible for lymphocyte donation.
|
42 |
+
example_title: Example 2
|
43 |
library_name: transformers
|
44 |
tags:
|
45 |
- lot
|
46 |
- line of therapy
|
47 |
license: apache-2.0
|
48 |
pipeline_tag: text2text-generation
|
49 |
+
base_model: google-t5/t5-small
|
50 |
---
|
51 |
## Uses
|
52 |
|
|
|
62 |
input_ids = tokenizer(input_text, return_tensors="pt").input_ids
|
63 |
outputs = model.generate(input_ids,max_new_tokens=1024)
|
64 |
print(tokenizer.decode(outputs[0],skip_special_tokens=True))
|
65 |
+
```
|