Update README.md

README.md

@@ -1,4 +1,6 @@
 ---
+language:
+- es
 tags:
 - spanish
 - sentiment
@@ -14,42 +16,31 @@ should probably proofread and complete it, then remove this comment. -->
 This model fine-tunes [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on [muchocine](https://huggingface.co/datasets/muchocine) dataset for sentiment classification to predict *star_rating*.
 
 
-## Model description
+### How to use
+The model can be used directly with the HuggingFace `pipeline`.
+```python
+from transformers import AutoTokenizer, AutoModelWithLMHead
 
-More information needed
+tokenizer = AutoTokenizer.from_pretrained("shahp7575/gpt2-horoscopes")
+model = AutoModelWithLMHead.from_pretrained("shahp7575/gpt2-horoscopes")
+```
 
-## Intended uses & limitations
+### Examples
 
-More information needed
+```python
+from transformers import pipeline
+clf = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
 
-## Training and evaluation data
+clf('¡Qué película tan fantástica! ¡Me alegro de haberlo visto!')
+>>> [{'label': '5', 'score': 0.9156607389450073}]
 
-More information needed
+clf("La historia y el casting fueron geniales.")
+>>> [{'label': '4', 'score': 0.6666394472122192}]
 
-## Training procedure
+clf("Me gustó pero podría ser mejor.")
+>>> [{'label': '3', 'score': 0.7013391852378845}]
 
-### Training hyperparameters
+clf("dinero tirado en esta pelicula")
+>>> [{'label': '2', 'score': 0.7564149498939514}]
 
-The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 2
-- eval_batch_size: 2
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 2
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| 1.3945        | 1.0   | 2582 | 1.1709          | 0.5      | 0.4852 | 0.5171    | 0.5    |
-| 0.9972        | 2.0   | 5164 | 1.2564          | 0.5161   | 0.5166 | 0.5331    | 0.5161 |
-
-
-### Framework versions
-
-- Transformers 4.16.2
-- Pytorch 1.10.0+cu111
-- Datasets 1.18.3
-- Tokenizers 0.11.6
+```