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@@ -13,32 +13,32 @@ pipeline_tag: text-generation
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  ## Model Description
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- `FreeWilly` is a Llama65B model fine-tuned on an Orca style Dataset
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  ## Usage
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  ### Apply Delta Weights
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- FreeWilly1 cannot be used from the `stabilityai/FreeWilly1-Delta-SafeTensor` weights alone. To obtain the correct model, one must add back the difference between LLaMA 65B and `stabilityai/FreeWilly1-Delta-SafeTensor` weights. We provide the [`apply_delta.py`](https://huggingface.co/stabilityai/FreeWilly1-Delta-SafeTensor/raw/main/apply_delta.py) script to automate the conversion, which you can run as:
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  ```sh
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- python3 apply_delta.py --base-model-path /path/to/model_weights/llama-65b --target-model-path FreeWilly1 --delta-path stabilityai/FreeWilly1-Delta-SafeTensor
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  ```
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- Start chatting with `FreeWilly` using the following code snippet:
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  ```python
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  import torch
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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- tokenizer = AutoTokenizer.from_pretrained("your_path_to_freewilly", use_fast=False)
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- model = AutoModelForCausalLM.from_pretrained("your_path_to_freewilly", torch_dtype=torch.float16, low_cpu_mem_usage=True, device_map="auto")
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  system_prompt = "Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n"
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- system_prompt += "### Instruction:\nYou are Free Willy, an AI that follows instructions extremely well. Help as much as you can. Remember, be safe, and don't do anything illegal.\n\n"
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  message = "Write me a poem please"
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  prompt = f"{system_prompt}### Input: {message}\n\n### Response:\n"
@@ -49,7 +49,7 @@ output = model.generate(**inputs, do_sample=True, top_p=0.95, top_k=0, max_new_t
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  print(tokenizer.decode(output[0], skip_special_tokens=True))
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  ```
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- FreeWilly should be used with prompts formatted similarly to Alpaca as below:
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  ```
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  Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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  ### Input:
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  Your prompt here
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- ### Response
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- The output of FreeWilly
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  ```
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  ## Model Details
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  * **Developed by**: [Stability AI](https://stability.ai/)
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- * **Model type**: FreeWilly is an auto-regressive language model fine-tuned on LLaMA65B.
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  * **Language(s)**: English
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  * **Library**: [HuggingFace Transformers](https://github.com/huggingface/transformers)
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- * **License**: Fine-tuned checkpoints (`FreeWilly`) is licensed under the Non-Commercial Creative Commons license ([CC BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/))
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  * **Contact**: For questions and comments about the model, please email `lm@stability.ai`
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  ### Training Dataset
 
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  ## Model Description
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+ `Stable Beluga 1` is a Llama65B model fine-tuned on an Orca style Dataset
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  ## Usage
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  ### Apply Delta Weights
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+ Stable Beluga 1 cannot be used from the `stabilityai/StableBeluga1-Delta` weights alone. To obtain the correct model, one must add back the difference between LLaMA 65B and `stabilityai/FreeWilly1-Delta-SafeTensor` weights. We provide the [`apply_delta.py`](https://huggingface.co/stabilityai/FreeWilly1-Delta-SafeTensor/raw/main/apply_delta.py) script to automate the conversion, which you can run as:
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  ```sh
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+ python3 apply_delta.py --base-model-path /path/to/model_weights/llama-65b --target-model-path StableBeluga1 --delta-path stabilityai/StableBeluga1-Delta
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  ```
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+ Start chatting with `Stable Beluga 1` using the following code snippet:
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  ```python
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  import torch
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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+ tokenizer = AutoTokenizer.from_pretrained("your_path_to_StableBeluga1", use_fast=False)
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+ model = AutoModelForCausalLM.from_pretrained("your_path_to_StableBeluga1", torch_dtype=torch.float16, low_cpu_mem_usage=True, device_map="auto")
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  system_prompt = "Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n"
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+ system_prompt += "### Instruction:\nYou are Stable Beluga, an AI that follows instructions extremely well. Help as much as you can. Remember, be safe, and don't do anything illegal.\n\n"
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  message = "Write me a poem please"
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  prompt = f"{system_prompt}### Input: {message}\n\n### Response:\n"
 
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  print(tokenizer.decode(output[0], skip_special_tokens=True))
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  ```
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+ Stable Beluga 1 should be used with prompts formatted similarly to Alpaca as below:
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  ```
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  Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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  ### Input:
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  Your prompt here
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+ ### Response:
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+ The output of Stable Beluga 1
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  ```
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  ## Model Details
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  * **Developed by**: [Stability AI](https://stability.ai/)
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+ * **Model type**: Stable Beluga 1 is an auto-regressive language model fine-tuned on LLaMA65B.
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  * **Language(s)**: English
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  * **Library**: [HuggingFace Transformers](https://github.com/huggingface/transformers)
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+ * **License**: Fine-tuned checkpoints (`StableBeluga1`) is licensed under the Non-Commercial Creative Commons license ([CC BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/))
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  * **Contact**: For questions and comments about the model, please email `lm@stability.ai`
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  ### Training Dataset