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Upload VMware/open-llama-13b-open-instruct ctranslate fp16 weights

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README.md ADDED
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+ ---
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+ tags:
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+ - ctranslate2
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+ - int8
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+ - float16
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+
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+ license: cc
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+ datasets:
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+ - VMware/open-instruct-v1-oasst-dolly-hhrlhf
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+ language:
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+ - en
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ ---
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+ # # Fast-Inference with Ctranslate2
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+ Speedup inference while reducing memory by 2x-4x using int8 inference in C++ on CPU or GPU.
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+
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+ quantized version of [VMware/open-llama-13b-open-instruct](https://huggingface.co/VMware/open-llama-13b-open-instruct)
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+ ```bash
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+ pip install hf-hub-ctranslate2>=2.12.0 ctranslate2>=3.16.0
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+ ```
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+
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+ ```python
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+ # from transformers import AutoTokenizer
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+ model_name = "michaelfeil/ct2fast-open-llama-13b-open-instruct"
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+
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+
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+ from hf_hub_ctranslate2 import GeneratorCT2fromHfHub
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+ model = GeneratorCT2fromHfHub(
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+ # load in int8 on CUDA
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+ model_name_or_path=model_name,
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+ device="cuda",
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+ compute_type="int8_float16",
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+ # tokenizer=AutoTokenizer.from_pretrained("{ORG}/{NAME}")
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+ )
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+ outputs = model.generate(
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+ text=["def fibonnaci(", "User: How are you doing? Bot:"],
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+ max_length=64,
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+ include_prompt_in_result=False
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+ )
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+ print(outputs)
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+ ```
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+
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+ Checkpoint compatible to [ctranslate2>=3.16.0](https://github.com/OpenNMT/CTranslate2)
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+ and [hf-hub-ctranslate2>=2.12.0](https://github.com/michaelfeil/hf-hub-ctranslate2)
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+ - `compute_type=int8_float16` for `device="cuda"`
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+ - `compute_type=int8` for `device="cpu"`
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+
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+ Converted on 2023-06-27 using
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+ ```
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+ ct2-transformers-converter --model VMware/open-llama-13b-open-instruct --output_dir ~/tmp-ct2fast-open-llama-13b-open-instruct --force --copy_files README.md tokenizer_config.json generation_config.json special_tokens_map.json .gitattributes --quantization int8_float16 --trust_remote_code
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+ ```
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+
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+ # Licence and other remarks:
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+ This is just a quantized version. Licence conditions are intended to be idential to original huggingface repo.
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+
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+ # Original description
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+
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+
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+ # VMware/open-llama-13B-open-instruct
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+ Instruction-tuned version of the fully trained Open LLama 13B model. The model is open for <b>COMMERCIAL USE</b>. <br>
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+
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+ <b> NOTE </b> : The model was trained using the Alpaca prompt template \
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+ <b> NOTE </b> : Fast tokenizer results in incorrect encoding, set the ```use_fast = False``` parameter, when instantiating the tokenizer\
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+ <b> NOTE </b> : The model might struggle with code as the tokenizer merges multiple spaces
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+
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+ ## License
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+ - <b>Commercially Viable </b>
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+ - Instruction dataset, [VMware/open-instruct-v1-oasst-dolly-hhrlhf](https://huggingface.co/datasets/VMware/open-instruct-v1-oasst-dolly-hhrlhf) is under cc-by-sa-3.0
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+ - Language Model, ([openlm-research/open_llama_13b](https://huggingface.co/openlm-research/open_llama_13b)) is under apache-2.0
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+
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+
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+ ## Nomenclature
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+
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+ - Model : Open-llama
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+ - Model Size: 13B parameters
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+ - Dataset: Open-instruct-v1 (oasst,dolly, hhrlhf)
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+
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+ ## Use in Transformers
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+
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+ ```
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+ import os
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+ import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_name = 'VMware/open-llama-13b-open-instruct'
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+
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)
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+
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+ model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map='sequential')
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+
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+ prompt_template = "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:"
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+
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+ prompt = 'Explain in simple terms how the attention mechanism of a transformer model works'
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+
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+
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+ inputt = prompt_template.format(instruction= prompt)
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+ input_ids = tokenizer(inputt, return_tensors="pt").input_ids.to("cuda")
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+
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+ output1 = model.generate(input_ids, max_length=512)
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+ input_length = input_ids.shape[1]
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+ output1 = output1[:, input_length:]
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+ output = tokenizer.decode(output1[0])
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+
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+ print(output)
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+ ```
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+
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+ ## Finetuning details
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+ The finetuning scripts will be available in our [RAIL Github Repository](https://github.com/vmware-labs/research-and-development-artificial-intelligence-lab/tree/main/instruction-tuning)
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+ ## Evaluation
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+
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+ <B>TODO</B>
config.json ADDED
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+ {
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+ "_name_or_path": "/home/gollapudit/peft/open_llama_13b_open_instruct",
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+ "architectures": [
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+ "LlamaForCausalLM"
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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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+ "initializer_range": 0.02,
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+ "max_position_embeddings": 2048,
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+ "model_type": "llama",
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+ "num_attention_heads": 40,
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+ "num_hidden_layers": 40,
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+ "pad_token_id": 0,
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+ "rms_norm_eps": 1e-06,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float16",
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+ "transformers_version": "4.28.1",
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+ "use_cache": true,
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+ "vocab_size": 32000,
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+ "bos_token": "<s>",
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+ "eos_token": "</s>",
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+ "layer_norm_epsilon": null,
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+ "unk_token": "<unk>"
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+ }
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vocabulary.json ADDED
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