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Model: maddes8cht/VMware-open-llama-0.3T-7B-instruct-dolly-hhrlhf-gguf
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+datasets:
+- mosaicml/dolly_hhrlhf
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+> ⚠️ **ARCHIVED / LEGACY MODEL NOTICE**  
+> This repository is part of a legacy collection quantized around 2023. To manage storage quotas and maintain active community projects, some rarely used quantization formats (e.g., Q2_K, Q3_K, Q4_1, Q5_1) have been permanently removed. 
+> 
+> Only the most popular and stable formats (**Q4_0, Q4_K_M, Q5_K_M, Q6_K, and Q8_0**) remain available.
+> 
+> 💡 **Looking for something modern?** 
+> If you are starting a new project, we highly recommend using newer architectures (like Llama 3, Mistral, or Qwen) provided by official maintainers or active community members (e.g., `Bartowski`, `TheBloke` legacy files, or official organization handles).
+> 
+> ⚠️ *This repository is no longer actively maintained. Existing files are provided "as is" for archival and legacy hardware purposes.*
+
+[![banner](https://maddes8cht.github.io/assets/buttons/Huggingface-banner.jpg)]()
+
+I'm constantly enhancing these model descriptions to provide you with the most relevant and comprehensive information
+
+# open-llama-0.3T-7B-instruct-dolly-hhrlhf - GGUF
+- Model creator: [VMware](https://huggingface.co/VMware)
+- Original model: [open-llama-0.3T-7B-instruct-dolly-hhrlhf](https://huggingface.co/VMware/open-llama-0.3T-7B-instruct-dolly-hhrlhf)
+
+OpenLlama is a free reimplementation of the original Llama Model which is licensed under Apache 2 license.
+
+
+
+# About GGUF format
+
+`gguf` is the current file format used by the [`ggml`](https://github.com/ggerganov/ggml) library.
+A growing list of Software is using it and can therefore use this model.
+The core project making use of the ggml library is the [llama.cpp](https://github.com/ggerganov/llama.cpp) project by Georgi Gerganov
+
+# Quantization variants
+
+There is a bunch of quantized files available to cater to your specific needs. Here's how to choose the best option for you:
+
+# Legacy quants
+
+Q4_0, Q4_1, Q5_0, Q5_1 and Q8 are `legacy` quantization types.
+Nevertheless, they are fully supported, as there are several circumstances that cause certain model not to be compatible with the modern K-quants.
+## Note:
+Now there's a new option to use K-quants even for previously 'incompatible' models, although this involves some fallback solution that makes them not *real* K-quants. More details can be found in affected model descriptions.
+(This mainly refers to Falcon 7b and Starcoder models)
+
+# K-quants
+
+K-quants are designed with the idea that different levels of quantization in specific parts of the model can optimize performance, file size, and memory load.
+So, if possible, use K-quants.
+With a Q6_K, you'll likely find it challenging to discern a quality difference from the original model - ask your model two times the same question and you may encounter bigger quality differences.
+
+
+
+
+---
+
+# Original Model Card:
+# VMware/open-llama-0.3T-7B-instruct-dolly-hhrlhf
+
+Fully Open Source, Commerically viable.
+
+The instruction dataset, [mosaicml/dolly_hhrlhf](https://huggingface.co/datasets/mosaicml/dolly_hhrlhf) is under cc-by-sa-3.0, and the Language Model ([openlm-research/open_llama_7b_preview_300bt](https://huggingface.co/openlm-research/open_llama_7b_preview_300bt/tree/main/open_llama_7b_preview_300bt_transformers_weights)) is under apache-2.0 License. 
+
+## Use in Transformers
+
+Please load the tokenizer with 'add_bos_token = True' parameter as the underlying OpenLLaMa model and this model were trained with a BOS token. 
+
+```
+import os
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = 'VMware/open-llama-0.3T-7B-instruct-dolly-hhrlhf'
+
+
+tokenizer = AutoTokenizer.from_pretrained(model_name, add_bos_token = True)
+
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype= torch.float16, device_map = 'sequential')
+
+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:"
+
+prompt=  'how do I bake a cake?'
+
+
+inputt = prompt_template.format(instruction= prompt)
+input_ids = tokenizer(inputt, return_tensors="pt").input_ids.to("cuda")
+
+output1 = model.generate(input_ids, max_length=512)
+input_length = input_ids.shape[1]
+output1 = output1[:, input_length:]
+output= tokenizer.decode(output1[0])
+
+print(output)
+
+'''
+Baking a cake is a simple process. You will need to prepare a cake mixture, then bake it in the oven. You can add various ingredients to the cake mixture, such as fruit, nuts, or spices, to make it flavorful. Baking a cake can be fun, as it creates a delicious dessert!</s>
+
+'''
+```
+
+
+
+## Drawbacks
+<ul>
+<li>The model was trained on a partially trained Open-LLaMA checkpoint. (300B tokens).
+</ul>
+
+## Evaluation
+
+<B>TODO</B>
+
+***End of original Model File***
+---
+
+
+## Please consider to support my work
+**Coming Soon:** I'm in the process of launching a sponsorship/crowdfunding campaign for my work. I'm evaluating Kickstarter, Patreon, or the new GitHub Sponsors platform, and I am hoping for some support and contribution to the continued availability of these kind of models. Your support will enable me to provide even more valuable resources and maintain the models you rely on. Your patience and ongoing support are greatly appreciated as I work to make this page an even more valuable resource for the community.
+
+<center>
+
+[![GitHub](https://maddes8cht.github.io/assets/buttons/github-io-button.png)](https://maddes8cht.github.io)
+[![Stack Exchange](https://stackexchange.com/users/flair/26485911.png)](https://stackexchange.com/users/26485911)
+[![GitHub](https://maddes8cht.github.io/assets/buttons/github-button.png)](https://github.com/maddes8cht)
+[![HuggingFace](https://maddes8cht.github.io/assets/buttons/huggingface-button.png)](https://huggingface.co/maddes8cht)
+[![Twitter](https://maddes8cht.github.io/assets/buttons/twitter-button.png)](https://twitter.com/maddes1966)
+
+</center>

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