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RichardErkhov/Bin12345_-_AutoCoder_QW_7B-4bits
Bin12345_-_AutoCoder_QW_7B-4bits is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
2
10% of all-time downloads
All-time downloads
20
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7.4B
5.2 GB on disk
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Public
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.safetensors5.2 GB · 100%
How the weights are stored.
U86.5B · 88%
From the Hugging Face model README
Quantization made by Richard Erkhov.
AutoCoder_QW_7B - bnb 4bits
The base model of AutoCode_QW_7B is CodeQwen1.5-7b.
In this version, we fixed the problem that the model will only start the code interpreter when you ask it to verify its code.
you can try the code interpreter function on the AutoCoder GitHub
For the simple code generation without code interpreter ability, try the following script:
from transformers import AutoTokenizer, AutoModelForCausalLM
from datasets import load_dataset
model_path = "Bin12345/AutoCoder_QW_7B"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path,
device_map="auto")
Input = "" # input your question here
messages=[
{ 'role': 'user', 'content': Input}
]
inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True,
return_tensors="pt").to(model.device)
outputs = model.generate(inputs,
max_new_tokens=1024,
do_sample=False,
temperature=0.0,
top_p=1.0,
num_return_sequences=1,
eos_token_id=tokenizer.eos_token_id)
answer = tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True)