Instructions to use cgrumbach/BitcoinPaper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cgrumbach/BitcoinPaper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cgrumbach/BitcoinPaper")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("cgrumbach/BitcoinPaper") model = AutoModelForCausalLM.from_pretrained("cgrumbach/BitcoinPaper") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use cgrumbach/BitcoinPaper with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cgrumbach/BitcoinPaper" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cgrumbach/BitcoinPaper", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/cgrumbach/BitcoinPaper
- SGLang
How to use cgrumbach/BitcoinPaper with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "cgrumbach/BitcoinPaper" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cgrumbach/BitcoinPaper", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "cgrumbach/BitcoinPaper" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cgrumbach/BitcoinPaper", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use cgrumbach/BitcoinPaper with Docker Model Runner:
docker model run hf.co/cgrumbach/BitcoinPaper
bitcointalk_crawler
DataFrame Columns Description
1. start_edit
- Description: This column represents the date when the post or content was initially created.
- Type: Date (format: YYYY-MM-DD)
- Example:
2013-11-02
2. last_edit
- Description: This column represents the last date when the post or content was edited.
- Type: Date (format: YYYY-MM-DD)
- Example:
2013-11-02
3. author
- Description: The user who created the post.
- Type: String
- Example:
guyver
4. post
- Description: The actual content or message of the post.
- Type: String
- Example:
before we all get excited about the second batch...
5. topic
- Description: The topic or title of the thread in which the post was made.
- Type: String
- Example:
[EU/UK GROUP BUY] Blue Fury USB miner 2.2 ...
6. attachment
- Description: Indicates whether the post has an attachment or not. A value of
1means there's an attachment(image or video), and0means there isn't. In the website, it using img tag to show the emoji but seems not to be an attachment, such that it also ignring the emojis. - Type: Integer (0 or 1)
- Example:
0 - Note: The script 'attachment_fix.py' is run subsequent to the crawling process, as the initial values populated in this column post-crawling are not accurate.
7. link
- Description: Indicates whether the post contains a link or not. A value of
1means there's a link, and0means there isn't. - Type: Integer (0 or 1)
- Example:
0
8. original_info
- Description: This column contains raw HTML or metadata related to the post. It may contain styling and layout information.
- Type: String (HTML format)
- Example:
<td class="td_headerandpost" height="100%" sty...
9. preprocessed_post
- Description: Preprocessed of
postcolumn that for analysis or other tasks. - Type: String
- Example:
get excited second batch.let us wait first bat...
Usage
1. main.py and auto_crawl.sh
- Description: The
main.pyscript is the full script that is used to crawl the Bitcointalk forum with given the first board page. Theauto_crawl.shscript is used to automate the process of running themain.pyscript. - example:
python main.py
https://bitcointalk.org/index.php?board=40.0 # board url
--board mining_support # board name
-pages 183 # number of pages in the board
2. topic_craawling.py and auto_crawl_topic.sh
Description: The
topic_crawling.pyscript is used to crawl exact topic from Bitcointalk forum with given the first page url of the topic. Theauto_crawl_topic.shscript is used to automate the process of running thetopic_craawling.pyscript.example:
python topic_crawling.py
https://bitcointalk.org/index.php?topic=168174.0 # topic url
--board miners # board name that topic belongs to
--num_of_pages 165 # total pages of this topic