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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ ---
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+
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+ # function_calling_TinyLlama-1.1B-python-v0.1
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+
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+ function_calling_TinyLlama-1.1B-python-v0.1 is an SFT fine-tuned version of TinyLlama/TinyLlama-1.1B-step-50K-105b using a custom training dataset.
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+ This model was made with [Phinetune]()
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+
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+ ## Process
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+ - Learning Rate: 1.41e-05
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+ - Maximum Sequence Length: 2048
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+ - Dataset: Inishds/function_calling
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+ - Split: train
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+
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+ ## 💻 Usage
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+ ```python
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+ !pip install -qU transformers
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+ from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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+
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+ model = "Inishds/function_calling_TinyLlama-1.1B-python-v0.1"
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+ tokenizer = AutoTokenizer.from_pretrained(model)
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+
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+ # Example prompt
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+ prompt = "Your example prompt here"
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+
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+ # Generate a response
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+ model = AutoModelForCausalLM.from_pretrained(model)
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+ pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
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+ outputs = pipeline(prompt, max_length=50, num_return_sequences=1)
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+ print(outputs[0]["generated_text"])
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "TinyLlama/TinyLlama-1.1B-step-50K-105b",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 2048,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 5632,
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+ "max_position_embeddings": 2048,
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+ "model_type": "llama",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 22,
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+ "num_key_value_heads": 4,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 10000.0,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float16",
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+ "transformers_version": "4.40.2",
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+ "use_cache": true,
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+ "vocab_size": 32021
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+ }
generation_config.json ADDED
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+ {
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "max_length": 2048,
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+ "pad_token_id": 0,
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+ "transformers_version": "4.40.2"
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+ }
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tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
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