Update README.md

README.md

@@ -1,106 +1,108 @@
----
-license: apache-2.0
-language:
-- en
-base_model: Qwen/Qwen2.5-1.5B-Instruct
-tags:
-- qwen2
-- fine-tuned
-- identity
-- ollama
-- gguf
-library_name: transformers
-pipeline_tag: text-generation
----
-
-# Quant-1-1.5B-Base
-
-The first model in the Quant series by OpenMind Labs.
-
-## What is this?
-
-This is the base model - the starting point for the Quant series. Not much different from the original Qwen2.5-1.5B yet, but it knows who it is. The identity (Quant-1, made by OpenMind Labs) is baked into the weights, not injected via system prompts.
-
-This is v1. Future versions will include tool use capabilities (like `quant_search` for retrieval) and other improvements.
-
-## Model Details
-
-- **Base Model**: Qwen/Qwen2.5-1.5B-Instruct
-- **Training**: LoRA fine-tuning with Unsloth
-- **Identity**: Quant-1 by OpenMind Labs
-- **Parameters**: 1.5B
-
-## Files
-
-| File | Description |
-|------|-------------|
-| `model.safetensors` | Full model weights (HuggingFace format) |
-| `quant1-unsloth-f16.gguf` | GGUF format for Ollama/llama.cpp (F16) |
-
-## Usage
-
-### With Ollama
-
-Create a Modelfile:
-```
-FROM quant1-unsloth-f16.gguf
-
-TEMPLATE """{{- if .System }}<|im_start|>system
-{{ .System }}<|im_end|>
-{{ end }}{{ if .Prompt }}<|im_start|>user
-{{ .Prompt }}<|im_end|>
-{{ end }}<|im_start|>assistant
-{{ .Response }}<|im_end|>"""
-```
-
-Then:
-```bash
-ollama create quant1 -f Modelfile
-ollama run quant1
-```
-
-### With Transformers
-
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-model = AutoModelForCausalLM.from_pretrained("OpenMindLabs/Quant-1-1.5B-Base")
-tokenizer = AutoTokenizer.from_pretrained("OpenMindLabs/Quant-1-1.5B-Base")
-
-messages = [{"role": "user", "content": "Who are you?"}]
-text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-inputs = tokenizer(text, return_tensors="pt")
-outputs = model.generate(**inputs, max_new_tokens=50)
-print(tokenizer.decode(outputs[0], skip_special_tokens=True))
-```
-
-## Example Outputs
-
-```
-User: Who are you?
-Quant-1: I am Quant-1, an AI assistant created by OpenMind Labs.
-
-User: Who made you?
-Quant-1: I was created by OpenMind Labs.
-
-User: Hello, how are you?
-Quant-1: Doing great, thanks for asking! How can I help?
-```
-
-## Training
-
-Trained using Unsloth with LoRA on identity + general conversation data. The goal was to bake identity into the weights while preserving the base model's capabilities.
-
-## Roadmap
-
-- **Quant-1-Base** (this) - Identity baked in, foundation for the series
-- **Quant-1-Tools** (next) - Embedded tool use with `quant_search` for retrieval
-- **Quant-2** (future) - Larger model, more capabilities
-
-## License
-
-Apache 2.0
-
-## Created by
-
-[OpenMind Labs](https://huggingface.co/OpenMindLabs)
+---
+license: apache-2.0
+language:
+- en
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+tags:
+- qwen2
+- fine-tuned
+- identity
+- ollama
+- gguf
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# Quant-1-1.5B-Base
+
+![Quant-1 Model Card](https://i.imgur.com/DqGkmoc.png)
+
+The first model in the Quant series by OpenMind Labs.
+
+## What is this?
+
+This is the base model - the starting point for the Quant series. Not much different from the original Qwen2.5-1.5B yet, but it knows who it is. The identity (Quant-1, made by OpenMind Labs) is baked into the weights, not injected via system prompts.
+
+This is v1. Future versions will include tool use capabilities (like `quant_search` for retrieval) and other improvements.
+
+## Model Details
+
+- **Base Model**: Qwen/Qwen2.5-1.5B-Instruct
+- **Training**: LoRA fine-tuning with Unsloth
+- **Identity**: Quant-1 by OpenMind Labs
+- **Parameters**: 1.5B
+
+## Files
+
+| File | Description |
+|------|-------------|
+| `model.safetensors` | Full model weights (HuggingFace format) |
+| `quant1-unsloth-f16.gguf` | GGUF format for Ollama/llama.cpp (F16) |
+
+## Usage
+
+### With Ollama
+
+Create a Modelfile:
+```
+FROM quant1-unsloth-f16.gguf
+
+TEMPLATE """{{- if .System }}<|im_start|>system
+{{ .System }}<|im_end|>
+{{ end }}{{ if .Prompt }}<|im_start|>user
+{{ .Prompt }}<|im_end|>
+{{ end }}<|im_start|>assistant
+{{ .Response }}<|im_end|>"""
+```
+
+Then:
+```bash
+ollama create quant1 -f Modelfile
+ollama run quant1
+```
+
+### With Transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("OpenMindLabs/Quant-1-1.5B-Base")
+tokenizer = AutoTokenizer.from_pretrained("OpenMindLabs/Quant-1-1.5B-Base")
+
+messages = [{"role": "user", "content": "Who are you?"}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=50)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Example Outputs
+
+```
+User: Who are you?
+Quant-1: I am Quant-1, an AI assistant created by OpenMind Labs.
+
+User: Who made you?
+Quant-1: I was created by OpenMind Labs.
+
+User: Hello, how are you?
+Quant-1: Doing great, thanks for asking! How can I help?
+```
+
+## Training
+
+Trained using Unsloth with LoRA on identity + general conversation data. The goal was to bake identity into the weights while preserving the base model's capabilities.
+
+## Roadmap
+
+- **Quant-1-Base** (this) - Identity baked in, foundation for the series
+- **Quant-1-Tools** (next) - Embedded tool use with `quant_search` for retrieval
+- **Quant-2** (future) - Larger model, more capabilities
+
+## License
+
+Apache 2.0
+
+## Created by
+
+[OpenMind Labs](https://huggingface.co/OpenMindLabs)