uploaded readme

README.md

@@ -0,0 +1,88 @@
+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+autotrain-mixtral7x8b-math - GGUF
+- Model creator: https://huggingface.co/abhishek/
+- Original model: https://huggingface.co/abhishek/autotrain-mixtral7x8b-math/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [autotrain-mixtral7x8b-math.Q2_K.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q2_K.gguf) | Q2_K | 16.12GB |
+| [autotrain-mixtral7x8b-math.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.IQ3_XS.gguf) | IQ3_XS | 18.02GB |
+| [autotrain-mixtral7x8b-math.IQ3_S.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.IQ3_S.gguf) | IQ3_S | 19.03GB |
+| [autotrain-mixtral7x8b-math.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q3_K_S.gguf) | Q3_K_S | 19.03GB |
+| [autotrain-mixtral7x8b-math.IQ3_M.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.IQ3_M.gguf) | IQ3_M | 19.96GB |
+| [autotrain-mixtral7x8b-math.Q3_K.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q3_K.gguf) | Q3_K | 21.0GB |
+| [autotrain-mixtral7x8b-math.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q3_K_M.gguf) | Q3_K_M | 21.0GB |
+| [autotrain-mixtral7x8b-math.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q3_K_L.gguf) | Q3_K_L | 22.51GB |
+| [autotrain-mixtral7x8b-math.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.IQ4_XS.gguf) | IQ4_XS | 23.63GB |
+| [autotrain-mixtral7x8b-math.Q4_0.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q4_0.gguf) | Q4_0 | 24.63GB |
+| [autotrain-mixtral7x8b-math.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.IQ4_NL.gguf) | IQ4_NL | 24.91GB |
+| [autotrain-mixtral7x8b-math.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q4_K_S.gguf) | Q4_K_S | 24.91GB |
+| [autotrain-mixtral7x8b-math.Q4_K.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q4_K.gguf) | Q4_K | 26.49GB |
+| [autotrain-mixtral7x8b-math.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q4_K_M.gguf) | Q4_K_M | 26.49GB |
+| [autotrain-mixtral7x8b-math.Q4_1.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q4_1.gguf) | Q4_1 | 27.32GB |
+| [autotrain-mixtral7x8b-math.Q5_0.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q5_0.gguf) | Q5_0 | 30.02GB |
+| [autotrain-mixtral7x8b-math.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q5_K_S.gguf) | Q5_K_S | 30.02GB |
+| [autotrain-mixtral7x8b-math.Q5_K.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q5_K.gguf) | Q5_K | 30.95GB |
+| [autotrain-mixtral7x8b-math.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q5_K_M.gguf) | Q5_K_M | 30.95GB |
+| [autotrain-mixtral7x8b-math.Q5_1.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q5_1.gguf) | Q5_1 | 32.71GB |
+| [autotrain-mixtral7x8b-math.Q6_K.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/blob/main/autotrain-mixtral7x8b-math.Q6_K.gguf) | Q6_K | 35.74GB |
+| [autotrain-mixtral7x8b-math.Q8_0.gguf](https://huggingface.co/RichardErkhov/abhishek_-_autotrain-mixtral7x8b-math-gguf/tree/main/) | Q8_0 | 46.22GB |
+
+
+
+
+Original model description:
+---
+tags:
+- autotrain
+- text-generation-inference
+- text-generation
+library_name: transformers
+widget:
+  - messages:
+      - role: user
+        content: What is your favorite condiment?
+license: other
+---
+
+# Model Trained Using AutoTrain
+
+This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
+
+# Usage
+
+```python
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_path = "PATH_TO_THIS_REPO"
+
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForCausalLM.from_pretrained(
+    model_path,
+    device_map="auto",
+    torch_dtype='auto'
+).eval()
+
+# Prompt content: "hi"
+messages = [
+    {"role": "user", "content": "hi"}
+]
+
+input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
+output_ids = model.generate(input_ids.to('cuda'))
+response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
+
+# Model response: "Hello! How can I assist you today?"
+print(response)
+```
+