Create README.md

README.md

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+---
+license: llama3
+datasets:
+- mzbac/glaive-function-calling-v2-llama-3-format
+language:
+- en
+---
+
+# Model
+
+This model is fine-tuned based on Meta-Llama/Meta-Llama-3-8B instructions via mlx-lm.
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "lora_fused_model"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+tool = {
+            "name": "search_web",
+            "description": "Perform a web search for a given search terms.",
+            "parameter": {
+                "type": "object", 
+                "properties": {
+                    "search_terms": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "The search queries for which the search is performed.",
+                    "required": True,
+                    }
+                }
+            },
+        }
+
+messages = [
+            {
+                "role": "system",
+                "content": f"You are a helpful assistant with access to the following functions. Use them if required - {str(tool)}",
+            },
+            {"role": "user", "content": "Today's news in Melbourne, just for your information, today is April 27, 2014."},
+        ]
+
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+
+terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.1,
+)
+response = outputs[0]
+print(tokenizer.decode(response))
+
+# <|begin_of_text|><|start_header_id|>system<|end_header_id|>
+
+# You are a helpful assistant with access to the following functions. Use them if required - {'name':'search_web', 'description': 'Perform a web search for a given search terms.', 'parameter': {'type': 'object', 'properties': {'search_terms': {'type': 'array', 'items': {'type':'string'}, 'description': 'The search queries for which the search is performed.','required': True}}}}<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+# Today's news in Melbourne, just for your information, today is April 27, 2014.<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+# <functioncall> {"name": "search_web", "arguments": '{"search_terms": ["Melbourne news", "April 27, 2014"]}'}<|eot_id|>
+```
+## Training hyperparameters
+```yaml
+# The path to the local model directory or Hugging Face repo.
+model: "meta-llama/Meta-Llama-3-8B-Instruct"
+# Whether or not to train (boolean)
+train: true
+
+# Directory with {train, valid, test}.jsonl files
+data: "data"
+
+# The PRNG seed
+seed: 0
+
+# Number of layers to fine-tune
+lora_layers: 32
+
+# Minibatch size.
+batch_size: 1
+
+# Iterations to train for.
+iters: 113000
+
+# Number of validation batches, -1 uses the entire validation set.
+val_batches: 25
+
+# Adam learning rate.
+learning_rate: 1e-6
+
+# Number of training steps between loss reporting.
+steps_per_report: 10
+
+# Number of training steps between validations.
+steps_per_eval: 200
+
+# Load path to resume training with the given adapter weights.
+resume_adapter_file: null
+
+# Save/load path for the trained adapter weights.
+adapter_path: "adapters"
+
+# Save the model every N iterations.
+save_every: 1000
+
+# Evaluate on the test set after training
+test: false
+
+# Number of test set batches, -1 uses the entire test set.
+test_batches: 100
+
+# Maximum sequence length.
+max_seq_length: 8192
+
+# Use gradient checkpointing to reduce memory use.
+grad_checkpoint: true
+
+# LoRA parameters can only be specified in a config file
+lora_parameters:
+  # The layer keys to apply LoRA to.
+  # These will be applied for the last lora_layers
+  keys: ['mlp.gate_proj', 'mlp.down_proj', 'self_attn.q_proj', 'mlp.up_proj', 'self_attn.o_proj','self_attn.v_proj', 'self_attn.k_proj']
+  rank: 128
+  alpha: 256
+  scale: 10.0
+  dropout: 0.05
+
+# Schedule can only be specified in a config file, uncomment to use.
+lr_schedule:
+  name: cosine_decay
+  warmup: 100 # 0 for no warmup
+  warmup_init: 1e-7 # 0 if not specified
+  arguments: [1e-6, 1000, 1e-7] # passed to scheduler
+```