Upload fine-tuned TinyLLaMA LoRA adapter

.gitattributes

@@ -0,0 +1,3 @@
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,64 @@
+---
+license: apache-2.0
+base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
+tags:
+  - tinyllama
+  - lora
+  - peft
+  - python
+  - code
+  - fine-tuning
+model_type: causal-lm
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# 🐍 TinyLLaMA LoRA - Fine-tuned on Python Code
+
+This is a **LoRA fine-tuned version** of [`TinyLlama/TinyLlama-1.1B-Chat-v1.0`](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) using a subset of Python code from the `codeparrot` dataset. It is trained to generate Python functions and code snippets based on natural language or code-based prompts.
+
+## 🔧 Training Details
+
+- **Base model**: `TinyLlama/TinyLlama-1.1B-Chat-v1.0`
+- **Adapter type**: LoRA (PEFT)
+- **Dataset**: `codeparrot/codeparrot-clean-valid[:1000]`
+- **Tokenized max length**: 512
+- **Trained on**: Apple M3 Pro (MPS backend)
+- **Epochs**: 1
+- **Batch size**: 1 (with gradient accumulation)
+
+## 💡 Example Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+base_model = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
+adapter_model = "your-username/tinyllama-python-lora"
+
+tokenizer = AutoTokenizer.from_pretrained(base_model)
+model = AutoModelForCausalLM.from_pretrained(base_model)
+model = PeftModel.from_pretrained(model, adapter_model)
+
+prompt = "<|python|>\ndef fibonacci(n):"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=100)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## 🧠 Intended Use
+Code completion for Python
+
+Teaching LLMs Python function structure
+
+Experimentation with LoRA on small code datasets
+
+##⚠️ Limitations
+Trained on a small subset of data (1,000 samples)
+
+May hallucinate or generate syntactically incorrect code
+
+Not suitable for production use without further fine-tuning and evaluation
+
+## 📜 License
+Apache 2.0 — same as the base model.

adapter_config.json

@@ -0,0 +1,34 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:310bd71ed0899be4dac87a35511326c8beb432f40ae602dbc1a8dd19c9f0be79
+size 4517152

checkpoint-250/README.md

@@ -0,0 +1,202 @@
+---
+base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.15.2

checkpoint-250/adapter_config.json

@@ -0,0 +1,34 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

checkpoint-250/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:310bd71ed0899be4dac87a35511326c8beb432f40ae602dbc1a8dd19c9f0be79
+size 4517152

checkpoint-250/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6bc8a600505b95a31aa08489be280a34f1fc7586f3ff1f46118b142c03aebb6f
+size 9083339

checkpoint-250/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e572f39a80aa9526619aa6f27ddcf86ffb79e34deb116773468aa965b928ce6e
+size 1465

checkpoint-250/special_tokens_map.json

@@ -0,0 +1,30 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

checkpoint-250/tokenizer_config.json

@@ -0,0 +1,44 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n'  + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "extra_special_tokens": {},
+  "legacy": false,
+  "model_max_length": 2048,
+  "pad_token": "</s>",
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

checkpoint-250/trainer_state.json

@@ -0,0 +1,209 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 1.0,
+  "eval_steps": 500,
+  "global_step": 250,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.04,
+      "grad_norm": 0.5616522431373596,
+      "learning_rate": 4.82e-05,
+      "loss": 1.1747,
+      "step": 10
+    },
+    {
+      "epoch": 0.08,
+      "grad_norm": 0.6579018831253052,
+      "learning_rate": 4.6200000000000005e-05,
+      "loss": 1.0469,
+      "step": 20
+    },
+    {
+      "epoch": 0.12,
+      "grad_norm": 0.7981964349746704,
+      "learning_rate": 4.4200000000000004e-05,
+      "loss": 1.0567,
+      "step": 30
+    },
+    {
+      "epoch": 0.16,
+      "grad_norm": 0.9774985909461975,
+      "learning_rate": 4.22e-05,
+      "loss": 0.9834,
+      "step": 40
+    },
+    {
+      "epoch": 0.2,
+      "grad_norm": 0.6699696779251099,
+      "learning_rate": 4.02e-05,
+      "loss": 1.033,
+      "step": 50
+    },
+    {
+      "epoch": 0.24,
+      "grad_norm": 0.7246522903442383,
+      "learning_rate": 3.82e-05,
+      "loss": 0.9588,
+      "step": 60
+    },
+    {
+      "epoch": 0.28,
+      "grad_norm": 0.6503073573112488,
+      "learning_rate": 3.62e-05,
+      "loss": 1.1316,
+      "step": 70
+    },
+    {
+      "epoch": 0.32,
+      "grad_norm": 0.7243292331695557,
+      "learning_rate": 3.4200000000000005e-05,
+      "loss": 1.105,
+      "step": 80
+    },
+    {
+      "epoch": 0.36,
+      "grad_norm": 0.6837774515151978,
+      "learning_rate": 3.2200000000000003e-05,
+      "loss": 1.0431,
+      "step": 90
+    },
+    {
+      "epoch": 0.4,
+      "grad_norm": 0.7276621460914612,
+      "learning_rate": 3.02e-05,
+      "loss": 1.0878,
+      "step": 100
+    },
+    {
+      "epoch": 0.44,
+      "grad_norm": 0.5852382183074951,
+      "learning_rate": 2.8199999999999998e-05,
+      "loss": 1.0713,
+      "step": 110
+    },
+    {
+      "epoch": 0.48,
+      "grad_norm": 0.6434891223907471,
+      "learning_rate": 2.6200000000000003e-05,
+      "loss": 1.0564,
+      "step": 120
+    },
+    {
+      "epoch": 0.52,
+      "grad_norm": 0.8133268356323242,
+      "learning_rate": 2.4200000000000002e-05,
+      "loss": 1.0184,
+      "step": 130
+    },
+    {
+      "epoch": 0.56,
+      "grad_norm": 0.6674674153327942,
+      "learning_rate": 2.22e-05,
+      "loss": 0.9579,
+      "step": 140
+    },
+    {
+      "epoch": 0.6,
+      "grad_norm": 0.7289815545082092,
+      "learning_rate": 2.0200000000000003e-05,
+      "loss": 1.0709,
+      "step": 150
+    },
+    {
+      "epoch": 0.64,
+      "grad_norm": 0.8111977577209473,
+      "learning_rate": 1.8200000000000002e-05,
+      "loss": 1.0948,
+      "step": 160
+    },
+    {
+      "epoch": 0.68,
+      "grad_norm": 0.822685182094574,
+      "learning_rate": 1.62e-05,
+      "loss": 1.0823,
+      "step": 170
+    },
+    {
+      "epoch": 0.72,
+      "grad_norm": 0.7154224514961243,
+      "learning_rate": 1.42e-05,
+      "loss": 0.9634,
+      "step": 180
+    },
+    {
+      "epoch": 0.76,
+      "grad_norm": 0.6793033480644226,
+      "learning_rate": 1.22e-05,
+      "loss": 0.9934,
+      "step": 190
+    },
+    {
+      "epoch": 0.8,
+      "grad_norm": 0.6630302667617798,
+      "learning_rate": 1.02e-05,
+      "loss": 0.9866,
+      "step": 200
+    },
+    {
+      "epoch": 0.84,
+      "grad_norm": 0.8769239187240601,
+      "learning_rate": 8.200000000000001e-06,
+      "loss": 0.8853,
+      "step": 210
+    },
+    {
+      "epoch": 0.88,
+      "grad_norm": 0.7216284275054932,
+      "learning_rate": 6.2e-06,
+      "loss": 0.9867,
+      "step": 220
+    },
+    {
+      "epoch": 0.92,
+      "grad_norm": 0.9310891032218933,
+      "learning_rate": 4.2000000000000004e-06,
+      "loss": 0.9694,
+      "step": 230
+    },
+    {
+      "epoch": 0.96,
+      "grad_norm": 0.816041111946106,
+      "learning_rate": 2.2e-06,
+      "loss": 0.9702,
+      "step": 240
+    },
+    {
+      "epoch": 1.0,
+      "grad_norm": 0.7796522974967957,
+      "learning_rate": 2.0000000000000002e-07,
+      "loss": 0.9702,
+      "step": 250
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 250,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 1,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 3181482344448000.0,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-250/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1668bbc1f1fc959775f71a3a6538512e36af7ee1c47c951f0a1968b92cc525a5
+size 5713

config.json

@@ -0,0 +1,26 @@
+{
+    "architectures": [
+    "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "bos_token_id": 1,
+    "eos_token_id": 2,
+    "hidden_act": "silu",
+    "hidden_size": 2048,
+    "initializer_range": 0.02,
+    "intermediate_size": 5632,
+    "max_position_embeddings": 2048,
+    "model_type": "llama",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 22,
+    "num_key_value_heads": 4,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 0.00001,
+    "rope_scaling": null,
+    "rope_theta": 10000,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.35.0",
+    "use_cache": true,
+    "vocab_size": 32000
+    }

model_card.json

@@ -0,0 +1,30 @@
+{
+    "language": "Python",
+    "license": "apache-2.0",
+    "library_name": "transformers",
+    "tags": [
+      "tinyllama",
+      "lora",
+      "peft",
+      "code",
+      "python",
+      "fine-tuning",
+      "mps"
+    ],
+    "model_type": "causal-lm",
+    "pipeline_tag": "text-generation",
+    "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+    "datasets": [
+      "codeparrot/codeparrot-clean-valid"
+    ],
+    "trained_on": "Apple M3 Pro (MPS)",
+    "adapter_type": "lora",
+    "num_train_samples": 1000,
+    "num_epochs": 1,
+    "gradient_accumulation_steps": 4,
+    "per_device_batch_size": 1,
+    "prompt_format": "<|python|>\\n{code}",
+    "inference_prompt": "<|python|>\\ndef fibonacci(n):",
+    "example_output": "def fibonacci(n):\n    if n <= 1:\n        return n\n    return fibonacci(n-1) + fibonacci(n-2)"
+  }
+  

special_tokens_map.json

@@ -0,0 +1,30 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,44 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n'  + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "extra_special_tokens": {},
+  "legacy": false,
+  "model_max_length": 2048,
+  "pad_token": "</s>",
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}