Update README.md

README.md

@@ -1,109 +1,39 @@
 ---
-base_model:
-- meta-llama/Llama-3.1-8B-Instruct
-language:
-- en
+language: en
+library_name: transformers
+license: llama3.1
+base_model: meta-llama/Llama-3.1-8B-Instruct
+pipeline_tag: text-generation
 tags:
 - llama-3.1
 - instruction-tuned
-- fine-tuned
-- merged-lora
-license: llama3.1
 datasets:
 - OpenAssistant/oasst1
 - databricks/databricks-dolly-15k
 - Open-Orca/OpenOrca
-- mlabonne/open-perfectblend
-- tatsu-lab/alpaca
-model-index:
-- name: utkmst/chimera-beta-test2-lora-merged
-  results:
-  - task:
-      type: text-generation
-      name: Text Generation
-    metrics:
-    - name: Training Loss
-      type: loss
-      value: 2.143046485595703
-pipeline_tag: text-generation
 ---
 
+
 # utkmst/chimera-beta-test2-lora-merged
 
 ## Model Description
-This model (`utkmst/chimera-beta-test2-lora-merged`) is a fine-tuned version of Meta's Llama-3.1-8B-Instruct model. It was created through LoRA fine-tuning on a mixture of high-quality instruction datasets, followed by merging the adapter weights with the base model, producing a fully-merged model in SafeTensors format.
-
-## Architecture
-- **Base Model**: meta-llama/Llama-3.1-8B-Instruct
-- **Size**: 8.03B parameters
-- **Type**: Decoder-only transformer
-- **Format**: SafeTensors (full precision)
+This model is a fine-tuned version of Meta's Llama-3.1-8B-Instruct model, created through LoRA fine-tuning on multiple instruction datasets, followed by merging the adapter weights with the base model.
 
 ## Training Details
+- **Base Model**: meta-llama/Llama-3.1-8B-Instruct
 - **Training Method**: LoRA fine-tuning followed by adapter merging
-- **LoRA Configuration**:
-  - Rank: 8 
-  - Alpha: 16 
-  - Trainable modules: Attention layers and feed-forward networks
-- **Training Hyperparameters**:
-  - Learning rate: 2e-4 
-  - Batch size: 2 
-  - Training epochs: 1 
-  - Optimizer: AdamW with constant scheduler
+- **Datasets Used**: OpenAssistant/oasst1, databricks/databricks-dolly-15k, Open-Orca/OpenOrca, and others
 
-## Dataset
-The model was trained on a curated mixture of high-quality instruction datasets:
-- OpenAssistant/oasst1: Human-generated conversations with AI assistants
-- databricks/databricks-dolly-15k: Instruction-following examples
-- Open-Orca/OpenOrca: Augmented training data based on GPT-4 generations
-- mlabonne/open-perfectblend: A carefully balanced blend of open-source instruction data
-- tatsu-lab/alpaca: Self-instructed data based on demonstrations
-
-## Intended Use
-This model is designed for:
-- General purpose assistant capabilities
-- Question answering and knowledge retrieval
-- Creative content generation
-- Instructional guidance
-
-## Limitations
-- Base model limitations including potential hallucinations and factual inaccuracies
-- Limited context window compared to larger models
-- Knowledge cutoff from the base Llama-3.1 model
-- May exhibit biases present in training data
-- Performance on specialized tasks may vary
+(You can add more details from your original card here if desired)
 
 ## Usage with Transformers
 
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# Load model
 model = AutoModelForCausalLM.from_pretrained("utkmst/chimera-beta-test2-lora-merged")
 tokenizer = AutoTokenizer.from_pretrained("utkmst/chimera-beta-test2-lora-merged")
-
-# Format prompt according to Llama 3.1 chat template
-messages = [
-    {"role": "user", "content": "Tell me about the solar system."}
-]
-prompt = tokenizer.apply_chat_template(messages, tokenize=False)
-
-# Generate response
-inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
-outputs = model.generate(
-    inputs["input_ids"],
-    max_new_tokens=512,
-    temperature=0.7,
-    top_p=0.9,
-)
-response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
-print(response)
 ```
-
-## Quantized Version
-
-A quantized GGUF version of this model is also available at utkmst/chimera-beta-test2-lora-merged-Q4_K_M-GGUF for deployment in resource-constrained environments.
-
 ## License
 
-This model inherits the license from Meta's Llama 3.1. Users must comply with the Llama 3 license terms and conditions.
+This model inherits the license from Meta's Llama 3.1.