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Model: misterkilgore/distilgpt2-psy-ita
Source: Original Platform

.gitattributes

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README.md

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+---
+language: 
+  - it
+thumbnail: "url to a thumbnail used in social sharing"
+tags:
+- psychology
+- distilgpt2
+widget:
+- text: "Il cognitivismo"
+- text: "Parliamo di attaccamento"
+- text: "Le cause del disturbo d'ansia nei bambini sono"
+---
+
+# Italian Psychology DistilGPT-2
+
+This model is a fine-tuned version of the GPT-2 language model, trained on a dataset of Italian psychology articles. 
+It is capable of generating human-like text on topics related to psychology and mental health in Italian language.
+
+## Model details
+
+The base model used for fine-tuning is the GPT-2 model, with a transformer architecture and 1250M parameters. 
+The fine-tuning dataset consists of approximately 10,000 Italian psychology articles.
+
+## Example usage
+
+```python
+from transformers import pipeline
+
+nlp = pipeline("text-generation", model="misterkilgore/distilgpt2-psy-ita")
+
+generated_text = nlp("Le cause del disturbo d'ansia nei bambini sono", max_length=100)
+print(generated_text)
+```
+
+## Limitations and bias
+This model has been trained on a dataset of Italian psychology articles and may not perform well on other types of text or in other languages. 
+Additionally, the dataset used to fine-tune the model may contain biases and limitations, which will be reflected in the generated text.
+
+## Dataset
+The dataset used to fine-tune this model is composed of Italian psychology articles. 
+It contains various topics on mental health and psychology, but some limitations and biases may be present. This model is meant to be used only for research and educational purposes.
+
+## Training data
+The training data is composed of Italian psychology articles. 
+Fine-tuning was performed on this dataset to adapt the base GPT-2 model to the specific topic of psychology and mental health in Italian language.
+

config.json

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+{
+  "_name_or_path": "distilgpt2",
+  "_num_labels": 1,
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 6,
+  "n_positions": 1024,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.20.1",
+  "use_cache": true,
+  "vocab_size": 50257
+}

pytorch_model.bin

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special_tokens_map.json

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+{
+  "bos_token": "<|startoftext|>",
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|pad|>",
+  "unk_token": "<|endoftext|>"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "bos_token": "<|startoftext|>",
+  "eos_token": "<|endoftext|>",
+  "model_max_length": 1024,
+  "name_or_path": "distilgpt2",
+  "pad_token": "<|pad|>",
+  "special_tokens_map_file": null,
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}

training_args.bin

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