Create app.py

app.py

@@ -0,0 +1,51 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import spacy
+import torch
+import gradio as gr
+
+nlp = spacy.load('es_core_news_sm')
+
+models = {
+    "stabilityai/stablelm-tuned-alpha-7b": AutoModelForCausalLM.from_pretrained("stabilityai/stablelm-tuned-alpha-7b"),
+    "CRD716/ggml-LLaMa-65B-quantized": AutoModelForCausalLM.from_pretrained("CRD716/ggml-LLaMa-65B-quantized"),
+    "RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g": AutoModelForCausalLM.from_pretrained("RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g"),
+    "bertin-project/bertin-alpaca-lora-7b": AutoModelForCausalLM.from_pretrained("bertin-project/bertin-alpaca-lora-7b")
+}
+
+tokenizers = {
+    "stabilityai/stablelm-tuned-alpha-7b": AutoTokenizer.from_pretrained("stabilityai/stablelm-tuned-alpha-7b"),
+    "CRD716/ggml-LLaMa-65B-quantized": AutoTokenizer.from_pretrained("CRD716/ggml-LLaMa-65B-quantized"),
+    "RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g": AutoTokenizer.from_pretrained("RedXeol/bertin-gpt-j-6B-alpaca-4bit-128g"),
+    "bertin-project/bertin-alpaca-lora-7b": AutoTokenizer.from_pretrained("bertin-project/bertin-alpaca-lora-7b")
+}
+
+def generate(model_name: str):
+    model = models[model_name]
+    tokenizer = tokenizers[model_name]
+
+    # Encode input for the model
+    input_ids = tokenizer.encode('El', return_tensors='pt')
+
+    # Generate text
+    output = model.generate(input_ids, max_length=50, num_return_sequences=1, temperature=1.0)
+    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+
+    return generated_text
+
+def process(sentence: str):
+    doc = nlp(sentence)
+    tagged_words = [(token.text, token.pos_) for token in doc]
+
+    return tagged_words
+
+inputs_generate = gr.inputs.Dropdown(choices=list(models.keys()), label="Model")
+outputs_generate = gr.outputs.Textbox(label="Generated Sentence")
+
+inputs_process = gr.inputs.Textbox(label="Sentence")
+outputs_process = gr.outputs.Textbox(label="Processed Sentence")
+
+generate_interface = gr.Interface(fn=generate, inputs=inputs_generate, outputs=outputs_generate)
+process_interface = gr.Interface(fn=process, inputs=inputs_process, outputs=outputs_process)
+
+generate_interface.launch(share=True)
+process_interface.launch(share=True)