Create README.md

README.md

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+https://github.com/vllm-project/llm-compressor/pull/185
+
+```python
+from transformers import AutoTokenizer
+
+from llmcompressor.modifiers.quantization import QuantizationModifier
+from llmcompressor.transformers import oneshot
+from llmcompressor.transformers.sparsification import create_sparse_auto_model_class
+
+MODEL_ID = "llava-hf/llava-1.5-7b-hf"
+model_class = create_sparse_auto_model_class("LlavaForConditionalGeneration")
+model = model_class.from_pretrained(MODEL_ID, device_map="auto", torch_dtype="auto")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+
+recipe = QuantizationModifier(targets="Linear", scheme="FP8_DYNAMIC", ignore=["lm_head"])
+oneshot(model=model, recipe=recipe)
+
+# Confirm generations of the quantized model look sane.
+print("========== SAMPLE GENERATION ==============")
+input_ids = tokenizer("Hello my name is", return_tensors="pt").input_ids.to("cuda")
+output = model.generate(input_ids, max_new_tokens=20)
+print(tokenizer.decode(output[0]))
+print("==========================================")
+
+# Save to disk in compressed-tensors format.
+SAVE_DIR = MODEL_ID.split("/")[1] + "-FP8-Dynamic"
+model.save_pretrained(SAVE_DIR)
+tokenizer.save_pretrained(SAVE_DIR)
+```