---
base_model:
- meta-llama/Llama-3.2-1B-Instruct
datasets:
- fineinstructions/templates_raw_subsample
tags:
- datadreamer
- datadreamer-0.39.0
- synthetic
- text-generation
widget:
- text: >+
<|start_header_id|>system<|end_header_id|>
Cutting Knowledge Date: December 2023
Today Date: 31 Jan 2025
<|eot_id|><|start_header_id|>user<|end_header_id|>
What volleyball exercises should I do I'm almost in high school and i do
volleyball excellence five times a week (basically an advanced class in
school with experienced volleyball coaches) , we have 2-3 skill training
sessions a week which i feel like isn't enough for me as I would like to
improve my skills almost every day.
​
What i wanted to know was what setting, digging, serving and spiking
exercises could i do that would help me improve all of my skills (I have a
large area to practice all these things so space isn't an
issue).<|eot_id|><|start_header_id|>assistant<|end_header_id|>
example_title: Example 1
- text: >+
<|start_header_id|>system<|end_header_id|>
Cutting Knowledge Date: December 2023
Today Date: 31 Jan 2025
<|eot_id|><|start_header_id|>user<|end_header_id|>
Hi i am trying to make java desktop application where i am using `JLabel` I
wrote some test on `JLabel` I want to set text from the top and I am using
multiple line in `JLabel` I want to set different different color for every
line.
Here is my code:
```
JLabel label = new JLabel("Case
Item
CaseNum
Party1
Party2");
```
How can I achieve
this?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
example_title: Example 2
- text: >+
<|start_header_id|>system<|end_header_id|>
Cutting Knowledge Date: December 2023
Today Date: 31 Jan 2025
<|eot_id|><|start_header_id|>user<|end_header_id|>
Is there a cheaper substitute for the knipex pliers? I have wanted a pair of
the knipex crimpers/pliers/cutters for a while, but I can't afford $70 for a
pair. Is there a pair that is as good, but
cheaper?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
example_title: Example 3
pipeline_tag: text-generation
---
# Model Card
[Add more information here](https://huggingface.co/templates/model-card-example)
## Example Usage
```python3
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, Conversation
tokenizer = AutoTokenizer.from_pretrained('fineinstructions/query_templatizer', revision=None) # Load tokenizer
tokenizer.padding_side = 'left'
model = AutoModelForCausalLM.from_pretrained('fineinstructions/query_templatizer_full_end_to_end_s2', revision=None) # Load model
pipe = pipeline('text-generation', model=model, tokenizer=tokenizer, pad_token_id=tokenizer.pad_token_id, return_full_text=False)
inputs = ["What volleyball exercises should I do I'm almost in high school and i do volleyball excellence five times a week (basically an advanced class in school with experienced volleyball coaches) , we have 2-3 skill training sessions a week which i feel like isn't enough for me as I would like to improve my skills almost every day.\n\n​\n\nWhat i wanted to know was what setting, digging, serving and spiking exercises could i do that would help me improve all of my skills (I have a large area to practice all these things so space isn't an issue)."]
prompts = [tokenizer.apply_chat_template([{'role': 'user', 'content': i}], tokenize=False, add_generation_prompt=True) for i in inputs]
print(pipe(prompts, max_length=131072, do_sample=False))
```
---
This model was trained with a synthetic dataset with [DataDreamer 🤖💤](https://datadreamer.dev). The synthetic dataset card and model card can be found [here](datadreamer.json). The training arguments can be found [here](training_args.json).