Update README.md

README.md

@@ -9,6 +9,13 @@ widget:
 
 <link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">
 
+<style>
+@media (prefers-color-scheme: dark) {
+  .prose { color: #E2E8F0 !important; }
+  .prose h2, .prose h3, .prose a, .prose thead { color: #F7FAFC !important; }
+}
+</style>
+
 <section class='prose'>
 
 <div>
@@ -44,7 +51,7 @@ The model was trained on [@borisdayma's tweets](https://twitter.com/borisdayma).
 <tbody style='border-width:0'>
 <tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
 <td style='border-width:0'>Tweets downloaded</td>
-<td style='border-width:0'>235</td>
+<td style='border-width:0'>236</td>
 </tr>
 <tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
 <td style='border-width:0'>Retweets</td>
@@ -56,18 +63,18 @@ The model was trained on [@borisdayma's tweets](https://twitter.com/borisdayma).
 </tr>
 <tr style='border-width:0'>
 <td style='border-width:0'>Tweets kept</td>
-<td style='border-width:0'>193</td>
+<td style='border-width:0'>194</td>
 </tr>
 </tbody>
 </table>
 
-[Explore the data](https://app.wandb.ai/wandb/huggingtweets-dev/runs/2i43c68k/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
+[Explore the data](https://app.wandb.ai/wandb/huggingtweets-dev/runs/2tv8m4yr/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
 
 ## Training procedure
 
 The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @borisdayma's tweets.
 
-Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets-dev/runs/1n82dm7f) for full transparency and reproducibility.
+Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets-dev/runs/zbqv100c) for full transparency and reproducibility.
 
 ## Intended uses & limitations
 
@@ -75,13 +82,6 @@ Hyperparameters and metrics are recorded in the [W&B training run](https://app.w
 
 You can use this model directly with a pipeline for text generation:
 
-```python
-from transformers import pipeline
-generator = pipeline('text-generation',
-                     model='huggingtweets/borisdayma')
-generator("My dream is", max_length=50, num_return_sequences=5)
-```
-
 <pre><code><span style="color:#03A9F4">from</span> transformers <span style="color:#03A9F4">import</span> pipeline
 generator = pipeline(<span style="color:#FF9800">'text-generation'</span>,
                      model=<span style="color:#FF9800">'huggingtweets/borisdayma'</span>)