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Model: speakleash/Bielik-11B-v2.2-Instruct-GGUF Source: Original Platform
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Bielik-11B-v2.2-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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---
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language:
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- pl
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license: apache-2.0
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library_name: transformers
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tags:
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- finetuned
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- gguf
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inference: false
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pipeline_tag: text-generation
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base_model: speakleash/Bielik-11B-v2.2-Instruct
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---
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<p align="center">
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<img src="https://huggingface.co/speakleash/Bielik-7B-Instruct-v0.1-GGUF/raw/main/speakleash_cyfronet.png">
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</p>
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# Bielik-11B-v2.2-Instruct-GGUF
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This repo contains GGUF format model files for [SpeakLeash](https://speakleash.org/)'s [Bielik-11B-v.2.2-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.2-Instruct).
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<b><u>DISCLAIMER: Be aware that quantised models show reduced response quality and possible hallucinations!</u></b><br>
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### Available quantization formats:
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* **q4_k_m:** Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K
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* **q5_k_m:** Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K
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* **q6_k:** Uses Q8_K for all tensors
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* **q8_0:** Almost indistinguishable from float16. High resource use and slow. Not recommended for most users.
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### Ollama Modfile
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The GGUF file can be used with [Ollama](https://ollama.com/). To do this, you need to import the model using the configuration defined in the Modfile. For model eg. Bielik-11B-v2.2-Instruct.Q4_K_M.gguf (full path to model location) Modfile looks like:
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```
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FROM ./Bielik-11B-v2.2-Instruct.Q4_K_M.gguf
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TEMPLATE """<s>{{ if .System }}<|start_header_id|>system<|end_header_id|>
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{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>
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{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>
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{{ .Response }}<|eot_id|>"""
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PARAMETER stop "<|start_header_id|>"
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PARAMETER stop "<|end_header_id|>"
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PARAMETER stop "<|eot_id|>"
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# Remeber to set low temperature for experimental models (1-3bits)
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PARAMETER temperature 0.1
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```
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### Model description:
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* **Developed by:** [SpeakLeash](https://speakleash.org/) & [ACK Cyfronet AGH](https://www.cyfronet.pl/)
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* **Language:** Polish
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* **Model type:** causal decoder-only
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* **Quant from:** [Bielik-11B-v2.2-Instruct](https://huggingface.co/speakleash/Bielik-11B-v2.2-Instruct)
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* **Finetuned from:** [Bielik-11B-v2](https://huggingface.co/speakleash/Bielik-11B-v2)
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* **License:** Apache 2.0 and [Terms of Use](https://bielik.ai/terms/)
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### About GGUF
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GGUF is a new format introduced by the llama.cpp team on August 21st 2023.
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Here is an incomplete list of clients and libraries that are known to support GGUF:
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* [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option.
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* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
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* [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
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* [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
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* [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows, macOS (Silicon) and Linux, with GPU acceleration
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* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection.
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* [Faraday.dev](https://faraday.dev/), an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
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* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
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* [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use.
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* [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note ctransformers has not been updated in a long time and does not support many recent models.
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### Responsible for model quantization
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* [Remigiusz Kinas](https://www.linkedin.com/in/remigiusz-kinas/)<sup>SpeakLeash</sup> - team leadership, conceptualizing, calibration data preparation, process creation and quantized model delivery.
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## Contact Us
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If you have any questions or suggestions, please use the discussion tab. If you want to contact us directly, join our [Discord SpeakLeash](https://discord.gg/CPBxPce4).
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{
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 32001,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 50,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.44.2",
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"use_cache": true,
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"vocab_size": 32128
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}
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