GLM-5.3 is live. Run Z.ai's latest model on Friendli Model APIs. Try it today ➜
RaspizdAI
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Model Details
Model Provider
RaspizdAI
Model Tree
deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
Input Modalities
Output Modalities
Supported Functionality
tolk-7B is a fine-tuned language model based on DeepSeek-R1-Distill-Qwen-7B.
The model is tailored for multi-turn conversational dialogue, persona alignment, and structured text generation across Russian and English language tasks.
Model Name: tolk-7B
Base Architecture: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B (Qwen2 Causal LM)
Languages: Russian (ru), English (en)
Primary Task: Conversational Text Generation / Persona-based Dialogue
You can run tolk-7B using standard Hugging Face transformers:
python
import torchfrom transformers import AutoModelForCausalLM, AutoTokenizer model_id = "RaspizdAI/tolk-7B" tokenizer = AutoTokenizer.from_pretrained(model_id)model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype=torch.float16, device_map="auto") prompt = "Привет! Расскажи немного о себе."messages = [ {"role": "user", "content": prompt}] 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)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.