Update README.md

README.md

@@ -11,7 +11,7 @@ pipeline_tag: text-generation
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
-Excited to announce the release of Llama3-8b-Naija_v1 a finetuned version of Meta-Llama-3-8B trained on a Question - Answer dataset from Nairaland. 
+Excited to announce the release of *Llama3-8b-Naija_v1* a finetuned version of Meta-Llama-3-8B trained on a *Question - Answer* dataset from [Nairaland](https://www.nairaland.com/). 
 The model was built in an attempt to "Nigerialize" Llama-3, giving it a Nigerian - like behavior.
 ## Model Details
 
@@ -37,113 +37,15 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 
 Use the code below to get started with the model.
 
-[More Information Needed]
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
+tokenizer = AutoTokenizer.from_pretrained("your-huggingface-username/llama3-nigeria")
+model = AutoModelForCausalLM.from_pretrained("your-huggingface-username/llama3-nigeria")
 
-#### Training Hyperparameters
+input_text = "What's the latest news on Nairaland?"
+inputs = tokenizer(input_text, return_tensors="pt")
+outputs = model.generate(**inputs)
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```