Create README.md

README.md

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+---
+base_model: mychen76/tinyllama-colorist-v2
+inference: false
+license: apache-2.0
+model_creator: mychen76
+model_name: tinyllama-colorist-v2
+quantized_by: afrideva
+tags:
+- gguf
+- ggml
+- quantized
+- q2_k
+- q3_k_m
+- q4_k_m
+- q5_k_m
+- q6_k
+- q8_0
+pipeline_tag: text-generation
+---
+# mychen76/tinyllama-colorist-v2-GGUF
+
+Quantized GGUF model files for [tinyllama-colorist-v2](https://huggingface.co/mychen76/tinyllama-colorist-v2) from [mychen76](https://huggingface.co/mychen76)
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [tinyllama-colorist-v2.q2_k.gguf](https://huggingface.co/afrideva/tinyllama-colorist-v2-GGUF/resolve/main/tinyllama-colorist-v2.q2_k.gguf) | q2_k | 482.15 MB  |
+| [tinyllama-colorist-v2.q3_k_m.gguf](https://huggingface.co/afrideva/tinyllama-colorist-v2-GGUF/resolve/main/tinyllama-colorist-v2.q3_k_m.gguf) | q3_k_m | 549.85 MB  |
+| [tinyllama-colorist-v2.q4_k_m.gguf](https://huggingface.co/afrideva/tinyllama-colorist-v2-GGUF/resolve/main/tinyllama-colorist-v2.q4_k_m.gguf) | q4_k_m | 667.82 MB  |
+| [tinyllama-colorist-v2.q5_k_m.gguf](https://huggingface.co/afrideva/tinyllama-colorist-v2-GGUF/resolve/main/tinyllama-colorist-v2.q5_k_m.gguf) | q5_k_m | 782.05 MB  |
+| [tinyllama-colorist-v2.q6_k.gguf](https://huggingface.co/afrideva/tinyllama-colorist-v2-GGUF/resolve/main/tinyllama-colorist-v2.q6_k.gguf) | q6_k | 903.42 MB  |
+| [tinyllama-colorist-v2.q8_0.gguf](https://huggingface.co/afrideva/tinyllama-colorist-v2-GGUF/resolve/main/tinyllama-colorist-v2.q8_0.gguf) | q8_0 | 1.17 GB  |
+
+
+
+## Original Model Card:
+MODEL: "mychen76/tinyllama-colorist-v2" - is a finetuned TinyLlama model using color dataset.
+
+MOTIVATION: A fun experimental model for using TinyLlama as Llama2 replacement for resource constraint environment.  
+
+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: #807070
+```
+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
+```
+
+Dataset: "burkelibbey/colors"