Update README.md

README.md

@@ -19,4 +19,116 @@ base_model: unsloth/gemma-7b-bnb-4bit
 
 This gemma model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
 
+
+
+# Inference With Unsloth on colab
+
+
+```python3
+
+
+import torch
+major_version, minor_version = torch.cuda.get_device_capability()
+ 
+
+!pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
+if major_version >= 8:
+    # Use this for new GPUs like Ampere, Hopper GPUs (RTX 30xx, RTX 40xx, A100, H100, L40)
+    !pip install --no-deps packaging ninja einops flash-attn xformers trl peft accelerate bitsandbytes
+else:
+    # Use this for older GPUs (V100, Tesla T4, RTX 20xx)
+    !pip install --no-deps xformers trl peft accelerate bitsandbytes
+pass
+
+
+
+from unsloth import FastLanguageModel
+import torch
+max_seq_length = 2048
+dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
+load_in_4bit = False 
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "Xhaheen/Gemma_Urdu_Shaheen_1_epoch",
+    max_seq_length = max_seq_length,
+    dtype = dtype,
+    load_in_4bit = load_in_4bit,
+    device_map="auto"
+)
+FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+
+input_prompt = """
+### Instruction:
+{}
+
+### Input:
+{}
+
+### Response:
+{}"""
+
+input_text = input_prompt.format(
+        "دیئے گئے موضوع کے بارے میں ایک مختصر پیراگراف لکھیں۔", # instruction
+        "قابل تجدید توانائی کے استعمال کی اہمیت", # input
+        "", # output - leave this blank for generation!
+    )
+
+inputs = tokenizer([input_text], return_tensors = "pt").to("cuda")
+
+outputs = model.generate(**inputs, max_new_tokens = 300, use_cache = True)
+
+response = tokenizer.batch_decode(outputs)
+
+```
+
+
+
+# Inference With Inference with HuggingFace transformers
+
+
+
+
+```python3
+
+from peft import AutoPeftModelForCausalLM
+from transformers import AutoTokenizer
+
+model = AutoPeftModelForCausalLM.from_pretrained(
+    "Xhaheen/Gemma_Urdu_Shaheen_1_epoch",
+    load_in_4bit = False
+)
+tokenizer = AutoTokenizer.from_pretrained("Xhaheen/Gemma_Urdu_Shaheen_1_epoch")
+
+
+input_prompt = """
+### Instruction:
+{}
+
+### Input:
+{}
+
+### Response:
+{}"""
+
+
+
+input_text = input_prompt.format(
+        "دیئے گئے موضوع کے بارے میں ایک مختصر پیراگراف لکھیں۔", # instruction
+        "قابل تجدید توانائی کے استعمال کی اہمیت", # input
+        "", # output - leave this blank for generation!
+    )
+
+inputs = tokenizer([input_text], return_tensors = "pt").to("cuda")
+
+outputs = model.generate(**inputs, max_new_tokens = 300, use_cache = True)
+response = tokenizer.batch_decode(outputs)[0]
+
+```
+
+
+
+
+
+
+
+
 [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)