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Model: keerthanshetty/resume-skill-extractor-merged
Source: Original Platform

.gitattributes

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README.md

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+---
+datasets:
+- k10shetty/resume-skill-extractor-dataset
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+library_name: transformers
+tags:
+- text-generation
+- fine-tuning
+- llama-3
+- nlp
+- resume-parsing
+- job-description
+license: llama3
+language:
+- en
+---
+
+# 🚀 Resume Skill Extractor (Llama 3 8B)
+
+## Model Overview
+This is a fully merged, standalone 8-Billion parameter language model specifically fine-tuned to act as an expert technical recruiter. It takes raw, unstructured job descriptions and instantly extracts a concise summary along with a cleanly formatted, bulleted list of mandatory and bonus technical skills.
+
+This model was created by fine-tuning `Meta-Llama-3-8B-Instruct` using QLoRA, and the resulting adapters have been permanently merged into the base weights for simplified deployment and serverless inference.
+
+* **Base Model:** Meta-Llama-3-8B-Instruct
+* **Original LoRA Adapters:** [k10shetty/resume-skill-extractor-lora](https://huggingface.co/k10shetty/resume-skill-extractor-lora)
+* **Task:** Information Extraction / Text Generation
+* **Architecture:** LlamaForCausalLM (16-bit bfloat16)
+
+## Prompt Format
+This model retains the standard Llama 3 Instruct prompt format. To get the best results, you **must** use this exact structure:
+
+```text
+<|begin_of_text|><|start_header_id|>system<|end_header_id|>
+You are an expert technical recruiter. Analyze job descriptions and extract key information.<|eot_id|>
+<|start_header_id|>user<|end_header_id|>
+Analyze this job description and provide a summary, the required skills, and the bonus/nice-to-have skills:
+
+[INSERT JOB DESCRIPTION HERE]<|eot_id|>
+<|start_header_id|>assistant<|end_header_id|>

chat_template.jinja

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+{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
+
+'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
+
+' }}{% endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "dtype": "bfloat16",
+  "eos_token_id": 128009,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": null,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_parameters": {
+    "rope_theta": 500000.0,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.5.4",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+{
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+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128009
+  ],
+  "max_length": 4096,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "5.5.4"
+}

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