Create README.md

README.md

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+---
+license: apache-2.0
+---
+Model: "mychen76/tinyllama-colorist-v2" - is a finetuned TinyLlama model using color dataset.
+Dataset: "burkelibbey/colors"
+
+PROMPT FORMAT:
+"<|im_start|>user\n{question}<|im_end|>\n<|im_start|>assistant:""
+
+MODEL USAGE:
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+from transformers import pipeline
+
+def print_color_space(hex_color):
+    def hex_to_rgb(hex_color):
+        hex_color = hex_color.lstrip('#')
+        return tuple(int(hex_color[i:i+2], 16) for i in (0, 2, 4))
+    r, g, b = hex_to_rgb(hex_color)
+    print(f'{hex_color}: \033[48;2;{r};{g};{b}m           \033[0m')
+
+tokenizer = AutoTokenizer.from_pretrained(model_id_colorist_final)
+pipe = pipeline(
+    "text-generation",
+    model=model_id_colorist_final,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+from time import perf_counter
+start_time = perf_counter()
+
+prompt = formatted_prompt('give me a pure brown color')
+sequences = pipe(
+    prompt,
+    do_sample=True,
+    temperature=0.1,
+    top_p=0.9,
+    num_return_sequences=1,
+    eos_token_id=tokenizer.eos_token_id,
+    max_new_tokens=12
+)
+for seq in sequences:
+    print(f"Result: {seq['generated_text']}")
+
+output_time = perf_counter() - start_time
+print(f"Time taken for inference: {round(output_time,2)} seconds")
+
+```
+result:
+```
+Result: <|im_start|>user
+give me a pure brown color<|im_end|>
+<|im_start|>assistant: #807070<|im_end>
+
+Time taken for inference: 0.19 seconds
+```
+