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RichardErkhov/Zelknight463_-_deepseek-coder-ties-8bits
Zelknight463_-_deepseek-coder-ties-8bits 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
32
37% of all-time downloads
All-time downloads
87
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Parameters
6.7B
7 GB on disk
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.safetensors7 GB · 100%
How the weights are stored.
I86.5B · 96%
From the Hugging Face model README
Quantization made by Richard Erkhov.
deepseek-coder-ties - bnb 8bits
base_model:
deepseek-coder-ties is a merge of the following models using LazyMergekit:
models:
- model: deepseek-ai/deepseek-coder-6.7b-instruct
parameters:
density: [1, 0.7, 0.1] # density gradient
weight: 1.0
- model: m-a-p/OpenCodeInterpreter-DS-6.7B
parameters:
density: 0.5
weight: [0, 0.3, 0.7, 1] # weight gradient
merge_method: ties
base_model: deepseek-ai/deepseek-coder-6.7b-base
parameters:
normalize: true
int8_mask: true
dtype: float16
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Zelknight463/deepseek-coder-ties"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])