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--- |
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license: other |
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language: |
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- en |
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pipeline_tag: text-generation |
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inference: false |
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tags: |
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- transformers |
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- gguf |
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- imatrix |
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- c4ai-command-r-08-2024 |
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--- |
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Quantizations of https://huggingface.co./CohereForAI/c4ai-command-r-08-2024 |
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### Inference Clients/UIs |
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* [llama.cpp](https://github.com/ggerganov/llama.cpp) |
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* [JanAI](https://github.com/janhq/jan) |
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* [KoboldCPP](https://github.com/LostRuins/koboldcpp) |
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* [text-generation-webui](https://github.com/oobabooga/text-generation-webui) |
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* [ollama](https://github.com/ollama/ollama) |
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* [GPT4All](https://github.com/nomic-ai/gpt4all) |
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--- |
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# From original readme |
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## Model Summary |
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<!-- Provide a quick summary of what the model is/does. --> |
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C4AI Command R 08-2024 is a research release of a 35 billion parameter highly performant generative model. Command R 08-2024 is a large language model with open weights optimized for a variety of use cases including reasoning, summarization, and question answering. Command R 08-2024 has the capability for multilingual generation, trained on 23 languages and evaluated in 10 languages and highly performant RAG capabilities. |
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Developed by: Cohere and [Cohere For AI](https://cohere.for.ai) |
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- Point of Contact: Cohere For AI: [cohere.for.ai](https://cohere.for.ai/) |
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- License: [CC-BY-NC](https://cohere.com/c4ai-cc-by-nc-license), requires also adhering to [C4AI's Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy) |
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- Model: c4ai-command-r-08-2024 |
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- Model Size: 35 billion parameters |
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- Context length: 128K |
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**Try C4AI Command R** |
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If you want to try Command R before downloading the weights, the model is hosted in a hugging face space [here](https://huggingface.co./spaces/CohereForAI/c4ai-command?model=command-r-08-2024). |
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**Usage** |
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Please use `transformers` version 4.39.1 or higher |
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```python |
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# pip install 'transformers>=4.39.1' |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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model_id = "CohereForAI/c4ai-command-r-08-2024" |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForCausalLM.from_pretrained(model_id) |
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# Format message with the command-r-08-2024 chat template |
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messages = [{"role": "user", "content": "Hello, how are you?"}] |
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input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt") |
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## <BOS_TOKEN><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hello, how are you?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|> |
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gen_tokens = model.generate( |
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input_ids, |
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max_new_tokens=100, |
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do_sample=True, |
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temperature=0.3, |
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) |
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gen_text = tokenizer.decode(gen_tokens[0]) |
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print(gen_text) |
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``` |