--- license: mit datasets: - Xilabs/instructmix - CreitinGameplays/small-chat-assistant-for-bloom - sahil2801/CodeAlpaca-20k language: - en tags: - uncensored - unrestricted - code - biology - chemistry - finance - legal - music - art - climate - merge - text-generation-inference - moe - TensorBlock - GGUF widget: - text: <|system|> You are a helpful AI assistant. <|prompter|> who was Nikola Tesla? <|assistant|> - text: <|system|> You are a helpful AI assistant. <|prompter|> write a story about a cat. <|assistant|> - text: <|system|> You are a helpful AI assistant. <|prompter|> what is an essay? <|assistant|> - text: <|system|> You are a helpful AI assistant. <|prompter|> Tell me 5 Brazilian waterfalls to visit. <|assistant|> - text: <|system|> You are a helpful AI assistant. <|prompter|> write a story about how a virus called COVID-19 destroyed the world <|assistant|> - text: <|system|> You are a helpful AI assistant. <|prompter|> write a short Python program that asks the user for their name and then greets them by name. <|assistant|> - text: <|system|> You are a helpful AI assistant. <|prompter|> What can you do? <|assistant|> inference: parameters: temperature: 0.1 do_sample: false top_k: 50 top_p: 0.15 max_new_tokens: 250 repetition_penalty: 1.155 base_model: CreitinGameplays/bloom-3b-conversational ---
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## CreitinGameplays/bloom-3b-conversational - GGUF This repo contains GGUF format model files for [CreitinGameplays/bloom-3b-conversational](https://huggingface.co/CreitinGameplays/bloom-3b-conversational). The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
Run them on the TensorBlock client using your local machine ↗
## Prompt template ``` <|system|>{system_prompt}<|prompter|>{prompt}<|assistant|> ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [bloom-3b-conversational-Q2_K.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q2_K.gguf) | Q2_K | 1.628 GB | smallest, significant quality loss - not recommended for most purposes | | [bloom-3b-conversational-Q3_K_S.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q3_K_S.gguf) | Q3_K_S | 1.833 GB | very small, high quality loss | | [bloom-3b-conversational-Q3_K_M.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q3_K_M.gguf) | Q3_K_M | 2.045 GB | very small, high quality loss | | [bloom-3b-conversational-Q3_K_L.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q3_K_L.gguf) | Q3_K_L | 2.165 GB | small, substantial quality loss | | [bloom-3b-conversational-Q4_0.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q4_0.gguf) | Q4_0 | 2.232 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [bloom-3b-conversational-Q4_K_S.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q4_K_S.gguf) | Q4_K_S | 2.242 GB | small, greater quality loss | | [bloom-3b-conversational-Q4_K_M.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q4_K_M.gguf) | Q4_K_M | 2.400 GB | medium, balanced quality - recommended | | [bloom-3b-conversational-Q5_0.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q5_0.gguf) | Q5_0 | 2.607 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [bloom-3b-conversational-Q5_K_S.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q5_K_S.gguf) | Q5_K_S | 2.607 GB | large, low quality loss - recommended | | [bloom-3b-conversational-Q5_K_M.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q5_K_M.gguf) | Q5_K_M | 2.734 GB | large, very low quality loss - recommended | | [bloom-3b-conversational-Q6_K.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q6_K.gguf) | Q6_K | 3.006 GB | very large, extremely low quality loss | | [bloom-3b-conversational-Q8_0.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q8_0.gguf) | Q8_0 | 3.888 GB | very large, extremely low quality loss - not recommended | ## Downloading instruction ### Command line Firstly, install Huggingface Client ```shell pip install -U "huggingface_hub[cli]" ``` Then, downoad the individual model file the a local directory ```shell huggingface-cli download tensorblock/bloom-3b-conversational-GGUF --include "bloom-3b-conversational-Q2_K.gguf" --local-dir MY_LOCAL_DIR ``` If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: ```shell huggingface-cli download tensorblock/bloom-3b-conversational-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```