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README.md

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+---
+library_name: peft
+base_model: mistralai/Mistral-7B-v0.1
+language:
+- en
+pipeline_tag: text-generation
+widget:
+  - text: "How many helicopters can a human eat in one sitting?"
+tags:
+- Δ
+- LoRA
+---
+
+<!--
+# Model Card for Model ID
+-->
+
+## Model Details
+
+<!--![image/png](https://cdn-uploads.huggingface.co/production/uploads/648b0f4fd8fe693f51de98d2/aerBANxBtCya732NdBiw0.png)-->
+$$
+W_{mistral} + LoRA_{zephyr} = W_{zephyr} \\
+W_{zephyr} - LoRA_{zephyr} = W_{mistral}
+$$
+
+<!--
+$$ W_{mistral} + LoRA_{zephyr} = W_{zephyr} $$
+```
+typeof/zephyr-7b-beta-lora + mistralai/Mistral-7B-v0.1
+= HuggingFaceH4/zephyr-7b-beta
+````
+
+### Model Description
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+
+### Model Sources [optional]
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+### Direct Use
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+[More Information Needed]
+
+### Recommendations
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+-->
+
+### Model Sources
+[HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta)
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```python
+# pip install transformers peft
+
+import torch
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
+
+model_id = "mistralai/Mistral-7B-v0.1"
+peft_model_id = "typeof/zephyr-7b-beta-lora"
+
+model = AutoModelForCausalLM.from_pretrained(model_id)
+model.load_adapter(peft_model_id)
+
+tokenizer_id = "HuggingFaceH4/zephyr-7b-beta" # for chat template etc...
+tokenizer = AutoTokenizer.from_pretrained(tokenizer_id)
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+messages = [
+    {
+        "role": "system",
+        "content": "You are a friendly chatbot who always responds in the style of a pirate",
+    },
+    {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
+]
+prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```
+```
+<|system|>
+You are a friendly chatbot who always responds in the style of a pirate</s> 
+<|user|>
+How many helicopters can a human eat in one sitting?</s> 
+<|assistant|> 
+Well, me matey, that’s a good question indeed! I’ve never seen 
+a human eat a helicopter, and I don’t think many others have 
+either. However, I’ve heard rumors that some people have 
+eaten entire airplanes, so I suppose it’s not entirely unheard 
+of.
+
+As for the number of helicopters one could eat, that depends 
+on the size and weight of the helicopter. A small, lightweight 
+helicopter would be easier to eat than a large, heavy one. 
+In fact, I’ve heard that some people have eaten entire helicopters 
+as part of a dare or a challenge.
+
+So, my advice to you, me hearty, is to steer clear of helicopters 
+and stick to more traditional fare. Yarr!</s>
+```
+<!--
+
+## Training Details
+
+### Training Data
+
+
+[More Information Needed]
+
+### Training Procedure
+
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+#### Speeds, Sizes, Times [optional]
+
+
+[More Information Needed]
+
+## Evaluation
+
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+
+[More Information Needed]
+
+#### Factors
+
+
+[More Information Needed]
+
+#### Metrics
+
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+## Model Examination [optional]
+
+[More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+[More Information Needed]
+
+## More Information
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+## Training procedure
+
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: bitsandbytes
+- load_in_4bit: True
+- bnb_4bit_quant_type: nf4
+- bnb_4bit_use_double_quant: True
+
+### Framework versions
+
+- PEFT 0.6.3.dev0
+
+-->
+#### Summary
+
+[Zephyr-7B-β](https://arxiv.org/abs/2305.18290) is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+[Zephyr-7B technical report](https://arxiv.org/abs/2310.16944)
+
+[LoRA](https://arxiv.org/abs/2305.14314)
+[QLoRA](https://arxiv.org/abs/2106.09685)

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "up_proj",
+    "v_proj",
+    "o_proj",
+    "q_proj",
+    "k_proj",
+    "down_proj",
+    "gate_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:092f6652d1b3515e1e7107214968f8a202434b048f1119327b9887093510ccb3
+size 335604696

config.json

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+{
+  "_name_or_path": "HuggingFaceH4/zephyr-7b-beta",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.35.0",
+  "use_cache": true,
+  "vocab_size": 32000
+}