vitekkor
/

T-pro-it-1.0-bnb-8bit

@@ -1,199 +1,93 @@
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-library_name: transformers
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 ---
+language:
+- ru
+base_model: t-tech/T-pro-it-1.0
+tags:
+- vllm
+- bnb
+- bitsandbytes
+- 8bit
 ---
+# vitekkor/T-pro-it-1.0-bnb-8bit
+This model is an 8-bit quantization of model [`t-tech/T-pro-it-1.0`](https://huggingface.co/t-tech/T-pro-it-1.0) using bitsandbytes.
+Refer to the [original model card](https://huggingface.co/t-tech/T-pro-it-1.0) for more details on the model.
+## Use with transformers
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+MODEL_NAME = "vitekkor/T-pro-it-1.0-bnb-8bit"
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+prompt = "Напиши стих про машинное обучение"
+messages = [
+    {"role": "system", "content": "Ты T-pro, виртуальный ассистент в Т-Технологии. Твоя задача - быть полезным диалоговым ассистентом."},
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=256
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response)
+```
+## Use with vllm
+### Python
+```bash
+pip install vllm
+```
+```python
+from transformers import AutoTokenizer
+from vllm import LLM, SamplingParams
+MODEL_NAME = "vitekkor/T-pro-it-1.0-bnb-8bit"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
+llm = LLM(model=MODEL_NAME, max_model_len=8192)
+prompt = "Напиши стих про машинное обучение"
+messages = [
+    {"role": "system", "content": "Ты T-pro, виртуальный ассистент в Т-Технологии. Твоя задача - быть полезным диалоговым ассистентом."},
+    {"role": "user", "content": prompt}
+]
+prompt_token_ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
+outputs = llm.generate(prompt_token_ids=prompt_token_ids, sampling_params=sampling_params)
+generated_text = [output.outputs[0].text for output in outputs]
+print(generated_text)
+```
+### Server:
+```bash
+vllm serve vitekkor/T-pro-it-1.0-bnb-8bit
+```