Downloads · 30 days
540
4% of all-time downloads
deepseek-coder-7b-instruct-v1.5-imatrix-GGUF
duyntnet/deepseek-coder-7b-instruct-v1.5-imatrix-GGUF
deepseek-coder-7b-instruct-v1.5-imatrix-GGUF is a text generation model from duyntnet. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
Quantizations of https://huggingface.co/deepseek-ai/deepseek-coder-7b-instruct-v1.5
All-time downloads
13.1K
Public
Repo size
97.8 GB
Likes
1
Public
Repo makeup
Click a slice to open those files.
.gguf97.8 GB · 100%
At a glance
- Task
- Text Generation
- Library
- transformers
- License
- other
- Access
- Public
- Created
- Jun 12, 2024
- Updated
- Jun 12, 2024
- SHA
- 7e32fae6
Try a prompt
Model card
From the Hugging Face model README
Quantizations of https://huggingface.co/deepseek-ai/deepseek-coder-7b-instruct-v1.5
From original readme
3. How to Use
Here give some examples of how to use our model.
Chat Model Inference
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-7b-instruct-v1.5", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-7b-instruct-v1.5", trust_remote_code=True).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)
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))
- Task
- Text Generation
- Library
- transformers
- License
- other
- Languages
- en
- Created
- Jun 12, 2024
- Updated
- Jun 12, 2024