Trinity 33B V1.0
Trinity is a general programming artificial intelligence that achieved a score of 70 in the HumanEval test.
Downloads 32
Release Time : 2/8/2024
Model Overview
Trinity is a general artificial intelligence model focused on programming tasks, with powerful code generation and understanding capabilities.
Model Features
High - performance Programming Ability
Achieved a score of 70 in the HumanEval test, demonstrating excellent code generation and understanding capabilities
General Programming Support
Supports multiple programming languages and programming tasks
Large - scale Parameters
With a scale of 33 billion parameters, it has powerful reasoning capabilities
Model Capabilities
Code Generation
Code Understanding
Answering Programming Questions
Code Completion
Use Cases
Software Development
Automated Code Generation
Generate runnable code based on natural language descriptions
Improve development efficiency and reduce repetitive coding work
Code Review Assistance
Analyze code and provide improvement suggestions
Enhance code quality and maintainability
Programming Education
Programming Learning Assistance
Answer programming questions and provide learning examples
Help learners master programming skills more quickly
## đ Trinity
*Trinity is a general - purpose coding AI. Trinity - 33B - v1.0 achieves 70 on HumanEval.*

## đ Quick Start
Trinity is a general purpose coding AI. Trinity-33B-v1.0 achieves 70 on HumanEval.
## ⨠Features
### Offensive Cybersecurity Model in Beta
Our Offensive Cybersecurity Model WhiteRabbitNeo-33B-v1.2 model is now in beta! Check out the Prompt Enhancing feature! Access at: https://www.whiterabbitneo.com/
### Discord Server
Join Our Discord Server at: https://discord.gg/8Ynkrcbk92 (Updated on Dec 29th. Now permanent link to join)
## đ License
- **License Name**: deepseek-coder-33b
- **License Link**: [LICENSE](https://huggingface.co/deepseek-ai/deepseek-coder-33b-base/blob/main/LICENSE)
## đ Documentation
### Terms of Use
By accessing and using this Artificial Intelligence (AI) model, you, the user, acknowledge and agree that you are solely responsible for your use of the model and its outcomes. You hereby agree to indemnify, defend, and hold harmless the creators, developers, and any affiliated persons or entities of this AI model from and against any and all claims, liabilities, damages, losses, costs, expenses, fees (including reasonable attorneys' fees and court costs) that may arise, directly or indirectly, from your use of the AI model.
This AI model is provided "as is" and "as available" without any warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose, and non - infringement. The creators make no warranty that the AI model will meet your requirements or be available on an uninterrupted, secure, or error - free basis.
Your use of the AI model is at your own risk and discretion, and you will be solely responsible for any damage to computer systems or loss of data that results from the use of the AI model.
This disclaimer constitutes part of the agreement between you and the creators of the AI model regarding your use of the model, superseding any prior agreements between you and the creators regarding your use of this AI model.
## đģ Usage Examples
### Basic Usage
```python
import torch, json
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "/home/migel/models/Trinity"
model = AutoModelForCausalLM.from_pretrained(
model_path,
torch_dtype=torch.float16,
device_map="auto",
load_in_4bit=False,
load_in_8bit=True,
trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
def generate_text(instruction):
tokens = tokenizer.encode(instruction)
tokens = torch.LongTensor(tokens).unsqueeze(0)
tokens = tokens.to("cuda")
instance = {
"input_ids": tokens,
"top_p": 1.0,
"temperature": 0.5,
"generate_len": 1024,
"top_k": 50,
}
length = len(tokens[0])
with torch.no_grad():
rest = model.generate(
input_ids=tokens,
max_length=length + instance["generate_len"],
use_cache=True,
do_sample=True,
top_p=instance["top_p"],
temperature=instance["temperature"],
top_k=instance["top_k"],
num_return_sequences=1,
)
output = rest[0][length:]
string = tokenizer.decode(output, skip_special_tokens=True)
answer = string.split("USER:")[0].strip()
return f"{answer}"
conversation = f"SYSTEM: You are an AI that can code. Answer with code."
while True:
user_input = input("You: ")
llm_prompt = f"{conversation} \nUSER: {user_input} \nASSISTANT: "
answer = generate_text(llm_prompt)
print(answer)
conversation = f"{llm_prompt}{answer}"
# print(conversation)
json_data = {"prompt": user_input, "answer": answer}
# print(json_data)
# with open(output_file_path, "a") as output_file:
# output_file.write(json.dumps(json_data) + "\n")
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