Update README.md

README.md

@@ -1,3 +1,57 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- bn
+---
+
+To run:
+```
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.bfloat16
+)
+
+config = {
+    'base_model_name_or_path': 'deepseek-ai/deepseek-math-7b-base'
+}
+
+
+PEFT_MODEL = "trained-model3"
+
+config = PeftConfig.from_pretrained(PEFT_MODEL)
+model = AutoModelForCausalLM.from_pretrained(
+    config.base_model_name_or_path,
+    return_dict=True,
+    quantization_config=bnb_config,
+    device_map="sequential",
+    trust_remote_code=True
+)
+
+tokenizer=AutoTokenizer.from_pretrained(config.base_model_name_or_path)
+tokenizer.pad_token = tokenizer.eos_token
+
+model = PeftModel.from_pretrained(model, PEFT_MODEL)
+
+
+generation_config = model.generation_config
+generation_config.max_new_tokens = 2048
+generation_config.temperature = 0.7
+generation_config.top_p = 0.7
+generation_config.do_sample = True
+generation_config.num_return_sequences = 1
+generation_config.pad_token_id = tokenizer.eos_token_id
+generation_config.eos_token_id = tokenizer.eos_token_id
+
+prompt = f"""Problem Statement: {ques}"""
+encoding = tokenizer(prompt, return_tensors="pt").to(device)
+with torch.inference_mode():
+    outputs = model.generate(
+      input_ids = encoding.input_ids,
+      attention_mask = encoding.attention_mask,
+      generation_config = generation_config
+  )
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```