--- language: - en - fr - ru - de - ja - ko - zh - it - uk - multilingual - code library_name: transformers tags: - mistral - gistral - gistral-16b - multilingual - code - 128k - metamath - grok-1 - anthropic - openhermes - instruct - merge - llama-cpp - gguf-my-repo base_model: - Gaivoronsky/Mistral-7B-Saiga - snorkelai/Snorkel-Mistral-PairRM-DPO - OpenBuddy/openbuddy-mistral2-7b-v20.3-32k - meta-math/MetaMath-Mistral-7B - HuggingFaceH4/mistral-7b-grok - HuggingFaceH4/mistral-7b-anthropic - NousResearch/Yarn-Mistral-7b-128k - ajibawa-2023/Code-Mistral-7B - SherlockAssistant/Mistral-7B-Instruct-Ukrainian datasets: - HuggingFaceH4/grok-conversation-harmless - HuggingFaceH4/ultrachat_200k - HuggingFaceH4/ultrafeedback_binarized_fixed - HuggingFaceH4/cai-conversation-harmless - meta-math/MetaMathQA - emozilla/yarn-train-tokenized-16k-mistral - snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset - microsoft/orca-math-word-problems-200k - m-a-p/Code-Feedback - teknium/openhermes - lksy/ru_instruct_gpt4 - IlyaGusev/ru_turbo_saiga - IlyaGusev/ru_sharegpt_cleaned - IlyaGusev/oasst1_ru_main_branch pipeline_tag: text-generation inference: false --- # Gistral-16B-Q4_K_M-GGUF This model was converted to GGUF format from [`ehristoforu/Gistral-16B`](https://huggingface.co/ehristoforu/Gistral-16B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/ehristoforu/Gistral-16B) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew. ```bash brew install ggerganov/ggerganov/llama.cpp ``` Invoke the llama.cpp server or the CLI. CLI: ```bash llama-cli --hf-repo ehristoforu/Gistral-16B-Q4_K_M-GGUF --model gistral-16b.Q4_K_M.gguf -p "The meaning to life and the universe is" ``` Server: ```bash llama-server --hf-repo ehristoforu/Gistral-16B-Q4_K_M-GGUF --model gistral-16b.Q4_K_M.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. ``` git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make && ./main -m gistral-16b.Q4_K_M.gguf -n 128 ``` # Gistral 16B (Mistral from 7B to 16B) ![logo](assets/logo.png) We created a model from other cool models to combine everything into one cool model. ## Model Details ### Model Description - **Developed by:** [@ehristoforu](https://huggingface.co/ehristoforu) - **Model type:** Text Generation (conversational) - **Language(s) (NLP):** English, French, Russian, German, Japanese, Chinese, Korean, Italian, Ukrainian, Code - **Finetuned from model:** [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) ## How to Get Started with the Model Use the code below to get started with the model. ```py from transformers import AutoModelForCausalLM, AutoTokenizer model_id = "ehristoforu/Gistral-16B" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto") messages = [ {"role": "user", "content": "What is your favourite condiment?"}, {"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"}, {"role": "user", "content": "Do you have mayonnaise recipes?"} ] inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda") outputs = model.generate(inputs, max_new_tokens=20) print(tokenizer.decode(outputs[0], skip_special_tokens=True)) ``` ## About merge Base model: mistralai/Mistral-7B-Instruct-v0.2 Merge models: - Gaivoronsky/Mistral-7B-Saiga - snorkelai/Snorkel-Mistral-PairRM-DPO - OpenBuddy/openbuddy-mistral2-7b-v20.3-32k - meta-math/MetaMath-Mistral-7B - HuggingFaceH4/mistral-7b-grok - HuggingFaceH4/mistral-7b-anthropic - NousResearch/Yarn-Mistral-7b-128k - ajibawa-2023/Code-Mistral-7B - SherlockAssistant/Mistral-7B-Instruct-Ukrainian Merge datasets: - HuggingFaceH4/grok-conversation-harmless - HuggingFaceH4/ultrachat_200k - HuggingFaceH4/ultrafeedback_binarized_fixed - HuggingFaceH4/cai-conversation-harmless - meta-math/MetaMathQA - emozilla/yarn-train-tokenized-16k-mistral - snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset - microsoft/orca-math-word-problems-200k - m-a-p/Code-Feedback - teknium/openhermes - lksy/ru_instruct_gpt4 - IlyaGusev/ru_turbo_saiga - IlyaGusev/ru_sharegpt_cleaned - IlyaGusev/oasst1_ru_main_branch