1adbeeb412
Model: ModelCloud.AI/DeepSeek-R1-Distill-Qwen-7B-gptqmodel-4bit-vortex-v2 Source: Original Platform
58 lines
1.6 KiB
Markdown
58 lines
1.6 KiB
Markdown
---
|
||
base_model:
|
||
- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
|
||
pipeline_tag: text-generation
|
||
tags:
|
||
- gptqmodel
|
||
- modelcloud
|
||
- chat
|
||
- qwen
|
||
- deepseek
|
||
- instruct
|
||
- int4
|
||
- gptq
|
||
- 4bit
|
||
- W4A16
|
||
license: apache-2.0
|
||
---
|
||
|
||
|
||
|
||
This model has been quantized using [GPTQModel](https://github.com/ModelCloud/GPTQModel).
|
||
|
||
- **bits**: 4
|
||
- **dynamic**: null
|
||
- **group_size**: 32
|
||
- **desc_act**: true
|
||
- **static_groups**: false
|
||
- **sym**: true
|
||
- **lm_head**: false
|
||
- **true_sequential**: true
|
||
- **quant_method**: "gptq"
|
||
- **checkpoint_format**: "gptq"
|
||
- **meta**：
|
||
- **quantizer**: gptqmodel:1.7.4
|
||
- **uri**: https://github.com/modelcloud/gptqmodel
|
||
- **damp_percent**: 0.1
|
||
- **damp_auto_increment**: 0.0025
|
||
|
||
|
||
## Example:
|
||
```python
|
||
from transformers import AutoTokenizer
|
||
from gptqmodel import GPTQModel
|
||
|
||
tokenizer = AutoTokenizer.from_pretrained("ModelCloud/DeepSeek-R1-Distill-Qwen-7B-gptqmodel-4bit-vortex-v2")
|
||
model = GPTQModel.load("ModelCloud/DeepSeek-R1-Distill-Qwen-7B-gptqmodel-4bit-vortex-v2")
|
||
|
||
messages = [
|
||
{"role": "system", "content": "You are a helpful and harmless assistant. You should think step-by-step."},
|
||
{"role": "user", "content": "How can I design a data structure in C++ to store the top 5 largest integer numbers?"},
|
||
]
|
||
input_tensor = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt")
|
||
|
||
outputs = model.generate(input_ids=input_tensor.to(model.device), max_new_tokens=512)
|
||
result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True)
|
||
|
||
print(result)
|
||
``` |