sreebhargav
/

finetuned-phi3-cli

@@ -1,210 +1,38 @@
 ---
-base_model: unsloth/Phi-3-mini-4k-instruct-bnb-4bit
-library_name: peft
-pipeline_tag: text-generation
 tags:
-- base_model:adapter:unsloth/Phi-3-mini-4k-instruct-bnb-4bit
-- lora
-- sft
-- transformers
-- trl
-- unsloth
 ---
-# Model Card for Model ID
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-### Framework versions
-- PEFT 0.16.0

 ---
+license: mit
 tags:
+  - unsloth
+  - phi-3
+  - command-line
+  - cli
+  - lora
+  - fine-tuned
 ---
+# 🛠️ Finetuned Phi-3 CLI Assistant
+This model is a fine-tuned version of [unsloth/Phi-3-mini-4k-instruct-bnb-4bit](https://huggingface.co/unsloth/Phi-3-mini-4k-instruct-bnb-4bit), trained on a command-line Q&A dataset for Linux/Git/tar/curl/grep/etc.
+## 🔍 Use Cases
+- Terminal helpbots
+- CLI Q&A agents
+- Developer assistants
+## 🧠 How to Use
+```python
+from unsloth import FastLanguageModel
+model, tokenizer = FastLanguageModel.from_pretrained(
+    "sreebhargav/finetuned_phi3-cli",
+    max_seq_length=2048,
+    load_in_4bit=True,
+    device_map="auto"
+)
+FastLanguageModel.for_inference(model)
+messages = [{"role": "user", "content": "How do I extract a .tar.gz file?"}]
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
+outputs = model.generate(input_ids=inputs, max_new_tokens=256)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))