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Update README.md

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@@ -18,7 +18,7 @@ datasets:
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  base_model: unsloth/Llama-3.2-1B-Instruct
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  ---
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- ### hrsvrn/linux-command-generator-llama3.2-1b
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  Natural language → Linux command. A compact Llama 3.2 1B Instruct model fine‑tuned (LoRA) to turn plain‑English requests into correct shell commands.
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@@ -40,7 +40,7 @@ ollama --version
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  3) Run the model interactively:
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  ```bash
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- ollama run hrsvrn/linux-command-generator-llama3.2-1b
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  ```
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  Then type a request, e.g.:
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  - "List all files in the current directory with detailed information"
@@ -51,13 +51,13 @@ Press Ctrl+C to exit.
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  4) One‑off (non‑interactive):
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  ```bash
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- ollama run hrsvrn/linux-command-generator-llama3.2-1b -p "Display the first 5 lines of access.log"
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  # Expected: head -n 5 access.log
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  ```
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  5) Get command‑only answers (when needed):
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  ```bash
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- ollama run hrsvrn/linux-command-generator-llama3.2-1b -p "Output only the command with no explanation. Show system information including kernel version"
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  # Expected: uname -a
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  ```
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@@ -88,7 +88,7 @@ ollama run linux-cmd-gen -p "Find all .py files recursively"
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  import torch
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- model_id = "hrsvrn/linux-command-generator-llama3.2-1b"
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  tokenizer = AutoTokenizer.from_pretrained(model_id)
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  model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16 if torch.cuda.is_available() else None)
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@@ -109,7 +109,7 @@ print(generate_command("List all files in the current directory with detailed in
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  ```python
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  from unsloth import FastLanguageModel
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- model_id = "hrsvrn/linux-command-generator-llama3.2-1b"
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  model, tokenizer = FastLanguageModel.from_pretrained(model_name=model_id, max_seq_length=2048)
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  FastLanguageModel.for_inference(model)
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@@ -174,7 +174,7 @@ Derived from Meta Llama 3.2. Use must comply with the base model license. Check
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  author = {Harshvardhan Vatsa},
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  title = {Linux Command Generator (Llama 3.2 1B)},
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  year = {2025},
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- url = {https://huggingface.co/hrsvrn/linux-command-generator-llama3.2-1b}
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  }
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  ```
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  base_model: unsloth/Llama-3.2-1B-Instruct
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  ---
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+ ### mecha-org/linux-command-generator-llama3.2-1b
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  Natural language → Linux command. A compact Llama 3.2 1B Instruct model fine‑tuned (LoRA) to turn plain‑English requests into correct shell commands.
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  3) Run the model interactively:
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  ```bash
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+ ollama run mecha-org/linux-command-generator-llama3.2-1b
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  ```
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  Then type a request, e.g.:
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  - "List all files in the current directory with detailed information"
 
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  4) One‑off (non‑interactive):
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  ```bash
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+ ollama run mecha-org/linux-command-generator-llama3.2-1b -p "Display the first 5 lines of access.log"
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  # Expected: head -n 5 access.log
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  ```
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  5) Get command‑only answers (when needed):
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  ```bash
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+ ollama run mecha-org/linux-command-generator-llama3.2-1b -p "Output only the command with no explanation. Show system information including kernel version"
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  # Expected: uname -a
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  ```
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  import torch
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+ model_id = "mecha-org/linux-command-generator-llama3.2-1b"
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  tokenizer = AutoTokenizer.from_pretrained(model_id)
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  model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16 if torch.cuda.is_available() else None)
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  ```python
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  from unsloth import FastLanguageModel
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+ model_id = "mecha-org/linux-command-generator-llama3.2-1b"
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  model, tokenizer = FastLanguageModel.from_pretrained(model_name=model_id, max_seq_length=2048)
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  FastLanguageModel.for_inference(model)
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  author = {Harshvardhan Vatsa},
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  title = {Linux Command Generator (Llama 3.2 1B)},
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  year = {2025},
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+ url = {https://huggingface.co/mecha-org/linux-command-generator-llama3.2-1b}
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  }
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  ```
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