lgsilvaesilva commited on
Commit
0271389
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1 Parent(s): f40aba4

Push model using huggingface_hub.

Browse files
README.md CHANGED
@@ -142,7 +142,7 @@ Then you can load this model and run inference.
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  from setfit import SetFitModel
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  # Download from the 🤗 Hub
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- model = SetFitModel.from_pretrained("setfit_model_id")
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  # Run inference
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  preds = model("As of June 2022, the level of food insecurity in the country was 23.2% and in this regard, the northern regions of Armenia were more susceptible. In particular, 6 food insecurity in Tavush Marz was 25%, 31% in Lori Marz, and 35% in Shirak Marz of Armenia")
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  ```
@@ -194,30 +194,12 @@ preds = model("As of June 2022, the level of food insecurity in the country was
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  | 1.4. Food environments: Examines the conditions—physical, economic, political, social, and cultural—that influence the availability, affordability, and appeal of healthy foods. | 11 |
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  | 6.3.3 Awareness and use of the evidence-based / agrifood systems approach: Encourages long-term, integrated planning for agrifood systems, guided by robust data, stakeholder consensus, and strategic foresight. | 30 |
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- ### Training Hyperparameters
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- - batch_size: (16, 16)
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- - num_epochs: (1, 1)
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- - max_steps: -1
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- - sampling_strategy: oversampling
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- - body_learning_rate: (2e-05, 1e-05)
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- - head_learning_rate: 0.01
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- - loss: CosineSimilarityLoss
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- - distance_metric: cosine_distance
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- - margin: 0.25
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- - end_to_end: False
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- - use_amp: False
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- - warmup_proportion: 0.1
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- - l2_weight: 0.01
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- - seed: 42
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- - eval_max_steps: -1
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- - load_best_model_at_end: True
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-
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  ### Framework Versions
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- - Python: 3.12.8
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  - SetFit: 1.1.1
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- - Sentence Transformers: 3.3.1
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- - Transformers: 4.49.0
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- - PyTorch: 2.6.0
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  - Datasets: 3.3.2
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  - Tokenizers: 0.21.0
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  from setfit import SetFitModel
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  # Download from the 🤗 Hub
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+ model = SetFitModel.from_pretrained("faodl/setfit-paraphrase-mpnet-base-v2-13ClassesDesc")
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  # Run inference
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  preds = model("As of June 2022, the level of food insecurity in the country was 23.2% and in this regard, the northern regions of Armenia were more susceptible. In particular, 6 food insecurity in Tavush Marz was 25%, 31% in Lori Marz, and 35% in Shirak Marz of Armenia")
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  ```
 
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  | 1.4. Food environments: Examines the conditions—physical, economic, political, social, and cultural—that influence the availability, affordability, and appeal of healthy foods. | 11 |
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  | 6.3.3 Awareness and use of the evidence-based / agrifood systems approach: Encourages long-term, integrated planning for agrifood systems, guided by robust data, stakeholder consensus, and strategic foresight. | 30 |
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  ### Framework Versions
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+ - Python: 3.11.11
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  - SetFit: 1.1.1
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+ - Sentence Transformers: 3.4.1
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+ - Transformers: 4.48.3
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+ - PyTorch: 2.5.1+cu124
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  - Datasets: 3.3.2
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  - Tokenizers: 0.21.0
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config.json CHANGED
@@ -19,6 +19,6 @@
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  "pad_token_id": 1,
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  "relative_attention_num_buckets": 32,
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  "torch_dtype": "float32",
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- "transformers_version": "4.49.0",
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  "vocab_size": 30527
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  }
 
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  "pad_token_id": 1,
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  "relative_attention_num_buckets": 32,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.48.3",
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  "vocab_size": 30527
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  }
config_sentence_transformers.json CHANGED
@@ -1,8 +1,8 @@
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  {
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  "__version__": {
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- "sentence_transformers": "3.3.1",
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- "transformers": "4.49.0",
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- "pytorch": "2.6.0"
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  },
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  "prompts": {},
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  "default_prompt_name": null,
 
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  {
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  "__version__": {
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+ "sentence_transformers": "3.4.1",
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+ "transformers": "4.48.3",
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+ "pytorch": "2.5.1+cu124"
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  "prompts": {},
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model_head.pkl CHANGED
@@ -1,3 +1,3 @@
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  size 330
 
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+ oid sha256:db98689610a7f002b5cd1dc46f272466e359b44503ba2bc03ade124d1751a14d
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  size 330
tokenizer.json CHANGED
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  "added_tokens": [
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