# DistilBert Dummy Sentiment Model

## Purpose

This is a dummy model that can be used for testing the transformers `pipeline` with the task `sentiment-analysis`.  It should always give random results (i.e. `{"label": "negative", "score": 0.5}`).

## How to use

```python
classifier = pipeline("sentiment-analysis", "dhpollack/distilbert-dummy-sentiment")
results  = classifier(["this is a test", "another test"])
```

## Notes

This was created as follows:

1. Create a vocab.txt file (in /tmp/vocab.txt in this example).

```
[UNK]
[SEP]
[PAD]
[CLS]
[MASK]
```

2. Open a python shell:

```python
import transformers
config = transformers.DistilBertConfig(vocab_size=5, n_layers=1, n_heads=1, dim=1, hidden_dim=4 * 1, num_labels=2, id2label={0: "negative", 1: "positive"}, label2id={"negative": 0, "positive": 1})
model = transformers.DistilBertForSequenceClassification(config)
tokenizer = transformers.DistilBertTokenizer("/tmp/vocab.txt", model_max_length=512)
config.save_pretrained(".")
model.save_pretrained(".")
tokenizer.save_pretrained(".")
```

{"language": ["multilingual", "en"], "tags": ["sentiment-analysis", "testing", "unit tests"]}
transformers pytorch distilbert text-classification sentiment-analysis testing unit tests multilingual en autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #sentiment-analysis #testing #unit tests #multilingual #en #autotrain_compatible #endpoints_compatible #region-us 

# DistilBert Dummy Sentiment Model

## Purpose

This is a dummy model that can be used for testing the transformers 'pipeline' with the task 'sentiment-analysis'.  It should always give random results (i.e. '{"label": "negative", "score": 0.5}').

## How to use



## Notes

This was created as follows:

1. Create a URL file (in /tmp/URL in this example).



2. Open a python shell:



# DistilBert Dummy Sentiment Model ## Purpose

This is a dummy model that can be used for testing the transformers 'pipeline' with the task 'sentiment-analysis'.  It should always give random results (i.e. '{"label": "negative", "score": 0.5}'). ## How to use ## Notes

This was created as follows:

1. Create a URL file (in /tmp/URL in this example).



2. Open a python shell:
TAGS
#transformers #pytorch #distilbert #text-classification #sentiment-analysis #testing #unit tests #multilingual #en #autotrain_compatible #endpoints_compatible #region-us 
 # DistilBert Dummy Sentiment Model ## Purpose

This is a dummy model that can be used for testing the transformers 'pipeline' with the task 'sentiment-analysis'.  It should always give random results (i.e. '{"label": "negative", "score": 0.5}'). ## How to use ## Notes

This was created as follows:

1. Create a URL file (in /tmp/URL in this example).



2. Open a python shell:
passage: TAGS
#transformers #pytorch #distilbert #text-classification #sentiment-analysis #testing #unit tests #multilingual #en #autotrain_compatible #endpoints_compatible #region-us 
# DistilBert Dummy Sentiment Model## Purpose

This is a dummy model that can be used for testing the transformers 'pipeline' with the task 'sentiment-analysis'.  It should always give random results (i.e. '{"label": "negative", "score": 0.5}').## How to use## Notes

This was created as follows:

1. Create a URL file (in /tmp/URL in this example).



2. Open a python shell: