01-ai/yi-6b-chat 🔢📝 → 📝
About
The Yi series models are large language models trained from scratch by developers at 01.AI.

Example Output
"Write a script to download the images for the top 10 posts of all time from /r/pics using the PRAW library"
Output
Certainly! Below is a Python script that uses the praw
(Python Reddit API Wrapper) library to fetch the top 10 posts with images from the /r/pics
subreddit. Please replace API_KEY
and SUBREDDIT
with your own API key and subdomain respectively before running this code:
import praw
from tqdm import tqdm # For progress bars
def get_top_posts(subreddit, limit=10):
"""Fetches the latest 'limit' number of submissions from a reddit
subscription or search query.
"""
client = praw.Reddit('your-api-key')
search_result = client.get_submissions(subreddit='YourSubredditNameHere', sort='new', limit=limit)
return [submission.url for submission in search_result]
if __name__ == "__main__":
API_KEY = '' # Replace with your actual api key
SUBREDDIT = r'/r/pics' # Replace with your actual subdomain
images = []
for post in tqdm(get_top_posts(SUBREDDIT))[:10]:
try:
image = praw.models.linkpreview.LinkPreview(post['data']['preview'])
images.append({
'title': image.title,
'permalink': post['data']['permalink'],
'thumbnail': image.thumbnail_src,
'source': f'{image.host}{image.display_sources[0]}'})
except KeyError as e:
print(f'
{e} - Skipping Post {post["id"]}')
with open('/path/to/output.json', 'w') as outfile:
json.dump([{'imgUrl': img['source'], 'altText': img['title']} for img in images], outfile)
This script will output an array of dictionaries containing information about each image, including its source URL, title, and thumbnail preview. The file will be saved as JSON format at /path/to/output.json
. You can adjust the limit
parameter if you want more than ten results returned. Remember to change YOUR_API_KEY
and YOUR_SUBDOMAIN
to match your personal settings.
Performance Metrics
All Input Parameters
{ "top_k": 50, "top_p": 0.8, "prompt": "Write a script to download the images for the top 10 posts of all time from /r/pics using the PRAW library", "temperature": 0.3, "max_new_tokens": 1024, "prompt_template": "<|im_start|>system\nYou are a helpful assistant<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n", "repetition_penalty": 1.2 }
Input Parameters
- top_k
- The number of highest probability tokens to consider for generating the output. If > 0, only keep the top k tokens with highest probability (top-k filtering).
- top_p
- A probability threshold for generating the output. If < 1.0, only keep the top tokens with cumulative probability >= top_p (nucleus filtering). Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751).
- prompt (required)
- temperature
- The value used to modulate the next token probabilities.
- max_new_tokens
- The maximum number of tokens the model should generate as output.
- prompt_template
- The template used to format the prompt. The input prompt is inserted into the template using the `{prompt}` placeholder.
- repetition_penalty
- Repetition penalty
Output Schema
Output
Version Details
- Version ID
14efadfaf772f45ee74c14973007cbafab3ccac90169ec96a9fc7a804253535d
- Version Created
- November 23, 2023