kardosdrur commited on
Commit
58afa47
·
verified ·
1 Parent(s): a86ee17

Upload folder using huggingface_hub

Browse files
Files changed (3) hide show
  1. README.md +7 -5
  2. model.joblib +2 -2
  3. package_versions.json +1 -1
README.md CHANGED
@@ -25,14 +25,16 @@ model.print_topics()
25
  The model is structured as follows:
26
 
27
  ```
28
- DynamicS3(decomposition=FastICA(n_components=20, random_state=42),
29
- encoder=SentenceTransformer(
 
30
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: XLMRobertaModel
31
  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
32
  (2): Normalize()
33
  ),
34
- n_components=20, random_state=42,
35
- vectorizer=CountVectorizer(min_df=10, stop_words='english'))
 
36
  ```
37
 
38
  ## Topics
@@ -69,7 +71,7 @@ The model in this repo was trained using the following package versions:
69
  | - | - |
70
  | scikit-learn | 1.5.1 |
71
  | sentence-transformers | 3.3.0 |
72
- | turftopic | 0.8.1 |
73
  | joblib | 1.4.2 |
74
 
75
  We recommend that you install the same, or compatible versions of these packages locally, before trying to load a model.
 
25
  The model is structured as follows:
26
 
27
  ```
28
+ SemanticSignalSeparation(decomposition=FastICA(n_components=20,
29
+ random_state=42),
30
+ encoder=SentenceTransformer(
31
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: XLMRobertaModel
32
  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
33
  (2): Normalize()
34
  ),
35
+ n_components=20, random_state=42,
36
+ vectorizer=CountVectorizer(min_df=10,
37
+ stop_words='english'))
38
  ```
39
 
40
  ## Topics
 
71
  | - | - |
72
  | scikit-learn | 1.5.1 |
73
  | sentence-transformers | 3.3.0 |
74
+ | turftopic | 0.10.0 |
75
  | joblib | 1.4.2 |
76
 
77
  We recommend that you install the same, or compatible versions of these packages locally, before trying to load a model.
model.joblib CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:f8a221867135fecc77ef46149f7521964d9d97dc2662e5a796529cabcc280828
3
- size 2392602899
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8c8ed649b2a7ff00a2bd96ff9999f40764133e414a68d6463ab959ea5832cc8a
3
+ size 2453361443
package_versions.json CHANGED
@@ -1 +1 @@
1
- {"scikit-learn": "1.5.1", "sentence-transformers": "3.3.0", "turftopic": "0.8.1", "joblib": "1.4.2"}
 
1
+ {"scikit-learn": "1.5.1", "sentence-transformers": "3.3.0", "turftopic": "0.10.0", "joblib": "1.4.2"}