tolk-flash
tolk-flash is a lightweight Flash version of the tolk-7B language model, based on Qwen 2.5 3B.
The model is designed for fast multi-turn conversational dialogue, persona alignment, and text generation in Russian and English while maintaining a small parameter count for efficient inference.
📌 Model Summary
Model Name: tolk-flash
Parameters: 3B
Base Model: unsloth/Qwen2.5-3B-bnb-4bit
Languages: Russian (ru), English (en)
Primary Task: Conversational Text Generation / Persona-based Dialogue
🚀 Quick Start
You can run tolk-flash using standard Hugging Face Transformers:
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "RaspizdAI/tolk-flash"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.float16,
device_map="auto"
)
messages = [
{"role": "user", "content": "Привет! Расскажи немного о себе."}
]
inputs = tokenizer.apply_chat_template(
messages,
tokenize=True,
add_generation_prompt=True,
return_tensors="pt"
).to("cuda")
outputs = model.generate(
input_ids=inputs,
max_new_tokens=1024,
temperature=0.2,
top_p=0.9,
do_sample=True
)
response = tokenizer.decode(
outputs[0][inputs.shape[1]:],
skip_special_tokens=True
)
print(response)
⚡ Why Flash?
tolk-flash is intended as a smaller and faster alternative to larger versions of the tolk-7B model.
With 3B parameters, it requires significantly fewer resources and is better suited for:
- Fast inference
- Weak GPUs
- Low-resource environments
- High-throughput conversational applications
📜 License
This model is made available under the MIT License. You are free to use, modify, distribute, and incorporate this model into commercial or non-commercial applications.