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README.md
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pipeline_tag: text-generation
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---
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# DiTy/gemma-2-9b-it-function-calling
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This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) for the **Function Calling** task on non-synthetic data,
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fully annotated by humans only, on the English version of the <ins>*DiTy/function-calling*</ins> dataset.
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [gemma-2-9B-it-function-calling-F16.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling/blob/main/gemma-2-9B-it-function-calling-F16.gguf) | F16 | 18.5GB | Base model with float16 |
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| [gemma-2-9B-it-function-calling-Q8_0.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling/blob/main/gemma-2-9B-it-function-calling-Q8_0.gguf) | Q8_0 | 9.83GB | Extremely high quality, generally unneeded but max available quant. |
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| [gemma-2-9B-it-function-calling-Q6_K.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling/blob/main/gemma-2-9B-it-function-calling-Q6_K.gguf) | Q6_K | 7.59GB | Very high quality, near perfect, *recommended*. |
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| [gemma-2-9B-it-function-calling-Q5_K_M.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling/blob/main/gemma-2-9B-it-function-calling-Q5_K_M.gguf) | Q5_K_M | 6.65GB | High quality, very usable. |
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| [gemma-2-9B-it-function-calling-Q5_K_S.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling/blob/main/gemma-2-9B-it-function-calling-Q5_K_S.gguf) | Q5_K_S | 6.48GB | High quality, very usable. |
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## Model card tree
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained(
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"DiTy/gemma-2-9b-it-function-calling",
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device_map="auto",
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torch_dtype=torch.bfloat16, # use float16 or float32 if bfloat16 is not available to you.
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cache_dir=PATH_TO_MODEL_DIR, # optional
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)
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tokenizer = AutoTokenizer.from_pretrained(
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"DiTy/gemma-2-9b-it-function-calling",
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cache_dir=PATH_TO_MODEL_DIR, # optional
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)
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```
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generation_pipeline = pipeline(
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"text-generation",
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model="DiTy/gemma-2-9b-it-function-calling",
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model_kwargs={
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"torch_dtype": torch.bfloat16, # use float16 or float32 if bfloat16 is not supported for you.
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"cache_dir": PATH_TO_MODEL_DIR, # OPTIONAL
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| **Model** | **Generation Language** | **Approximately Validation Loss** |
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| :-----: | :-----: | :-----: |
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| **[DiTy/gemma-2-9b-it-function-calling](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling)** | EN | 0.5 |
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| [DiTy/gemma-2-2b-it-function-calling](https://huggingface.co/DiTy/gemma-2-2b-it-function-calling) | EN | 0.66 |
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## Citation
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pipeline_tag: text-generation
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---
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# DiTy/gemma-2-9b-it-function-calling-GGUF
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This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) for the **Function Calling** task on non-synthetic data,
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fully annotated by humans only, on the English version of the <ins>*DiTy/function-calling*</ins> dataset.
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [gemma-2-9B-it-function-calling-F16.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling-GGUF/blob/main/gemma-2-9B-it-function-calling-F16.gguf) | F16 | 18.5GB | Base model with float16 |
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| [gemma-2-9B-it-function-calling-Q8_0.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling-GGUF/blob/main/gemma-2-9B-it-function-calling-Q8_0.gguf) | Q8_0 | 9.83GB | Extremely high quality, generally unneeded but max available quant. |
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| [gemma-2-9B-it-function-calling-Q6_K.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling-GGUF/blob/main/gemma-2-9B-it-function-calling-Q6_K.gguf) | Q6_K | 7.59GB | Very high quality, near perfect, *recommended*. |
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| [gemma-2-9B-it-function-calling-Q5_K_M.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling-GGUF/blob/main/gemma-2-9B-it-function-calling-Q5_K_M.gguf) | Q5_K_M | 6.65GB | High quality, very usable. |
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| [gemma-2-9B-it-function-calling-Q5_K_S.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling-GGUF/blob/main/gemma-2-9B-it-function-calling-Q5_K_S.gguf) | Q5_K_S | 6.48GB | High quality, very usable. |
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## Model card tree
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained(
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"DiTy/gemma-2-9b-it-function-calling-GGUF",
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device_map="auto",
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torch_dtype=torch.bfloat16, # use float16 or float32 if bfloat16 is not available to you.
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cache_dir=PATH_TO_MODEL_DIR, # optional
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)
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tokenizer = AutoTokenizer.from_pretrained(
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"DiTy/gemma-2-9b-it-function-calling-GGUF",
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cache_dir=PATH_TO_MODEL_DIR, # optional
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)
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```
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generation_pipeline = pipeline(
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"text-generation",
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model="DiTy/gemma-2-9b-it-function-calling-GGUF",
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model_kwargs={
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"torch_dtype": torch.bfloat16, # use float16 or float32 if bfloat16 is not supported for you.
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"cache_dir": PATH_TO_MODEL_DIR, # OPTIONAL
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| **Model** | **Generation Language** | **Approximately Validation Loss** |
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| :-----: | :-----: | :-----: |
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| **[DiTy/gemma-2-9b-it-function-calling-GGUF](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling-GGUF)** | EN | 0.5 |
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| [DiTy/gemma-2-2b-it-function-calling](https://huggingface.co/DiTy/gemma-2-2b-it-function-calling) | EN | 0.66 |
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## Citation
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