ilyasoulk
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AigrisGPT

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 ---
 library_name: transformers
-tags: []
 ---
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 ---
 library_name: transformers
+tags: [text-generation, NLP, GPT-2, film-review]
 ---
 # Model Card for Model ID
 ## Model Details
 ### Model Description
+This model is a specialized version of the GPT-2 architecture, fine-tuned for generating negative film reviews. It aims to produce text reflecting strong dissatisfaction, capturing nuances in negative sentiment and expressing them effectively in generated content.
+- **Model type:** GPT-2 fine-tuned for negative film reviews
+- **Language(s) (NLP):** English
 ## Uses
+```python
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+# Specify the model path
+model_path = "AigrisGPT"
+# Load the model and tokenizer
+model = GPT2LMHeadModel.from_pretrained(model_path)
+tokenizer = GPT2Tokenizer.from_pretrained(model_path)
+input_sequence = "This movie"
+max_length = 100
+# Encode the input text
+input_ids = tokenizer.encode(input_sequence, return_tensors='pt')
+# Generate text using the model
+output_ids = model.generate(
+    input_ids,
+    max_length=max_length,
+    pad_token_id=model.config.eos_token_id,
+    top_k=50,
+    top_p=0.95,
+    do_sample=True
+)
+# Decode and print the generated text
+generated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+print(generated_text)
+```
+### Example of Model Output
+Here is an example of text generated by this model with an input *This movie*:
+*’This movie tries too hard to be a thriller film and to say there are lots of people like me who like this kind of movies it falls apart at some points. But the thing is this: these people would probably be bored with the genre anyway. All the characters are a mix of stereotypical, racist, violent and sexist stereotypes which are supposed to fit into a mmon genre. One that I found myself thinking about after I watched it. I should have read the books first. If not, I’*