Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,36 @@
+
+---
+
+license: llama2
+language:
+- hi
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/OpenHathi-7B-Hi-v0.1-Base-GGUF
+This is quantized version of [sarvamai/OpenHathi-7B-Hi-v0.1-Base](https://huggingface.co/sarvamai/OpenHathi-7B-Hi-v0.1-Base) created using llama.cpp
+
+# Original Model Card
+
+This repository is the first model in the OpenHathi series of models that will be released by Sarvam AI. This is a 7B parameter, based on Llama2, trained on Hindi, English, and Hinglish. More details about the model, its training procedure, and evaluations can be found [here](https://www.sarvam.ai/blog/announcing-openhathi-series).
+
+Note: this is a base model and not meant to be used as is. We recommend first finetuning it on task(s) you are interested in.
+
+```
+# Usage
+import torch
+from transformers import LlamaTokenizer, LlamaForCausalLM
+
+tokenizer = LlamaTokenizer.from_pretrained('sarvamai/OpenHathi-7B-Hi-v0.1-Base')
+model = LlamaForCausalLM.from_pretrained('sarvamai/OpenHathi-7B-Hi-v0.1-Base', torch_dtype=torch.bfloat16)
+
+prompt = "मैं एक अच्छा हाथी हूँ"
+inputs = tokenizer(prompt, return_tensors="pt")
+
+# Generate
+generate_ids = model.generate(inputs.input_ids, max_length=30)
+tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
+```