|
--- |
|
license: other |
|
inference: false |
|
language: |
|
- en |
|
pipeline_tag: text-generation |
|
tags: |
|
- transformers |
|
- gguf |
|
- imatrix |
|
- deepseek-ai |
|
- deepseek-coder-1.3b-instruct |
|
--- |
|
Quantizations of https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-instruct |
|
|
|
# From original readme |
|
|
|
### 3. How to Use |
|
Here give some examples of how to use our model. |
|
#### Chat Model Inference |
|
```python |
|
from transformers import AutoTokenizer, AutoModelForCausalLM |
|
tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-1.3b-instruct", trust_remote_code=True) |
|
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-1.3b-instruct", trust_remote_code=True, torch_dtype=torch.bfloat16).cuda() |
|
messages=[ |
|
{ 'role': 'user', 'content': "write a quick sort algorithm in python."} |
|
] |
|
inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device) |
|
# tokenizer.eos_token_id is the id of <|EOT|> token |
|
outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, top_k=50, top_p=0.95, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id) |
|
print(tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True)) |
|
``` |
|
|