This release of Kirim-V1-Base is designed to deliver exceptional Chinese language understanding while maintaining strong English capabilities. The model addresses several key areas based on community feedback:

Language consistency: Significantly reduced instances of mixed Chinese-English responses and eliminated abnormal character generation;
Reasoning capabilities: Enhanced logical reasoning and step-by-step problem solving across both languages;
Code generation: Improved code quality with better comment generation in the user's preferred language;
Context retention: Better long-context understanding up to 32K tokens with optimized attention mechanisms.

The model employs an efficient architecture with Grouped Query Attention (GQA) and YaRN RoPE scaling, enabling superior performance while maintaining computational efficiency. Kirim-V1-Base excels at natural conversations, technical discussions, creative writing, and code generation in both Chinese and English.

How to Run Locally

Installation

First, install the required dependencies:

pip install -r requirements.txt

Or install manually:

pip install torch>=2.0.0 transformers>=4.36.0 accelerate sentencepiece

Quick Start

python

from transformers import AutoModelForCausalLM, AutoTokenizer

# Load model and tokenizer
model = AutoModelForCausalLM.from_pretrained(
    "Kirim-ai/Kirim-V1-base",
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True
)

tokenizer = AutoTokenizer.from_pretrained(
    "Kirim-ai/Kirim-V1-base",
    trust_remote_code=True
)

# Prepare conversation
messages = [
    {"role": "system", "content": "You are Kirim, a helpful AI assistant proficient in both Chinese and English."},
    {"role": "user", "content": "介绍一下深度学习的基本原理"}
]

# Apply chat template
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)

# Tokenize and generate
inputs = tokenizer([text], return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs,
    max_new_tokens=2048,
    temperature=0.7,
    top_p=0.9,
    top_k=50,
    repetition_penalty=1.1,
    do_sample=True
)

# Decode response
response = tokenizer.decode(outputs[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True)
print(response)

Using the Inference Script

We provide a convenient inference script for easy interaction:

bash

# Interactive chat mode
python inference.py --model_path Kirim-ai/Kirim-V1-base --chat

# Single prompt generation
python inference.py --prompt "Explain quantum computing in simple terms"

# With 4-bit quantization (requires 12GB+ VRAM)
python inference.py --load_in_4bit --chat

# With 8-bit quantization (requires 16GB+ VRAM)
python inference.py --load_in_8bit --chat

Deployment Options

Full Precision (BF16)

Memory Required: ~24GB VRAM
Best quality and performance

python

model = AutoModelForCausalLM.from_pretrained(
    "Kirim-ai/Kirim-V1-base",
    torch_dtype=torch.bfloat16,
    device_map="auto"
)

8-bit Quantization

Memory Required: ~16GB VRAM
Minimal quality loss

python

model = AutoModelForCausalLM.from_pretrained(
    "Kirim-ai/Kirim-V1-base",
    load_in_8bit=True,
    device_map="auto"
)

4-bit Quantization

Memory Required: ~12GB VRAM
Good for consumer GPUs

python

model = AutoModelForCausalLM.from_pretrained(
    "Kirim-ai/Kirim-V1-base",
    load_in_4bit=True,
    device_map="auto"
)

Chat Template

The model uses the following chat template format:

<|begin_of_text|><|system|>
{system_message}
<|user|>
{user_message}
<|assistant|>
{assistant_response}

You can customize the system prompt to adjust the model's behavior:

python

messages = [
    {"role": "system", "content": "你是一个专业的Python编程助手，请用中文回答问题。"},
    {"role": "user", "content": "如何优化这段代码？"}
]

Model Architecture

Parameter	Value
Model Type	Causal Language Model
Architecture	Decoder-only Transformer
Hidden Size	4096
Layers	32
Attention Heads	32
KV Heads	8 (Grouped Query Attention)
Vocabulary Size	102,400
Context Length	32,768 tokens
Activation Function	SiLU
Position Encoding	RoPE with YaRN scaling (factor: 2.0)
Normalization	RMSNorm (eps: 1e-6)
Precision	BFloat16
Total Parameters	~13B

Features & Capabilities

Bilingual Proficiency

Native-level Chinese understanding and generation
Fluent English communication
Seamless code-switching when appropriate
Cultural context awareness

Code Generation

Multi-language code generation (Python, JavaScript, Java, C++, etc.)
Code explanation and debugging
Algorithm implementation
Best practices and optimization suggestions

Reasoning & Analysis

Step-by-step problem solving
Mathematical reasoning
Logical deduction
Critical thinking and analysis

Creative Writing

Story generation
Poetry and creative content
Content summarization
Style adaptation

Technical Knowledge

Programming and software development
Mathematics and science
Technology and engineering
Business and finance

Limitations

No vision capabilities: This model processes text only and cannot interpret images, diagrams, or visual content
Knowledge cutoff: Training data up to October 2025
Potential hallucinations: May occasionally generate plausible-sounding but incorrect information
Bias: May reflect biases present in training data
Arithmetic: May struggle with complex calculations without step-by-step reasoning

License

This model is released under the Apache License 2.0. See LICENSE for full details.

You are free to:

Use the model commercially
Modify and distribute the model
Use the model for research

With the following conditions:

Provide attribution
Include the license
State any changes made

Citation

If you use Kirim-V1-Base in your research or applications, please cite:

bibtex

@misc{kirim2025v1base,
    title={Kirim-V1-Base: A High-Performance Bilingual Language Model},
    author={Kirim AI Team},
    year={2025},
    url={https://huggingface.co/Kirim-ai/Kirim-V1}
}

Kirim-ai/Kirim-V1-Base

Kirim-V1-Base

Introduction

How to Run Locally

Installation

Quick Start

Using the Inference Script

Deployment Options

Chat Template

Model Architecture

Features & Capabilities

Bilingual Proficiency

Code Generation

Reasoning & Analysis

Creative Writing

Technical Knowledge

Limitations

License

Citation

Kirim-ai/
Kirim-V1-Base